Research
Natural Language Processing, Natural Language Processes
Computational Neuroscience
Data Mining
Human Brain, Human Brains
Brain Activation, Brain Activity
Computational Linguistics
Statistical Analysis
Artificial Intelligence Approach
Plos One
Big Data
Web Search
Statistical Model, Statistical Modelling, Statistical Modeling, Statistical Models
Supervised Learning
Improved Learning, Improving Learning
Business Media
Fmri Data
Knowledge Discovery
Information Extraction
Knowledge Base Relations
Brain Regions
Multivariate Analysis
Cognitive Processes, Cognitive Processing
Social Interactions, Social Interaction
World Wide Web
Pattern Recognition, Pattern Recognit
W Casey
Interpersonal Relations
Computer Vision
Narrative Summaries
Intensive Model
Semantic Web
Neural Code, Neural Coding
Knowledge Management
Exploring Commonalities
Cognitive State, Cognitive States
Computational Models, Computer Modeling, Computational Modeling, Computational Model, Computer Model, Computer Modelling, Computer Models, Computational Modelling
Human Computer, Human Computation, Human Computing
Quantitative Modeling, Quantitative Models, Quantitative Model
Change Detection
Second Generation
Extracted Information
Machine Learning Research
Extra Information
Transcription Factors, Transcription Factor
Americas Security
St Century
Y Huang
Neural Activity
Multiple Study
User Activity, Users Activities
Human Teachers
Educational Technologies, Educational Technology
Tailored Feedback
Data Analysis Project
Computational Molecular
Discovery Science
Brain Imaging, Brain Images
Ongoing Activities
Bayesian Networks, Bayesian Network
Extracting Knowledge
Relational Domains
Active Learning
Users Projects
Prior Knowledge
Graphical Models
Domain Expertise
Student Perceptions, Students Perceptions, Students Perception
Single Trial
Cognitive Style, Cognitive Styles
Individual Differences
American Medical Informatics
Single Subject
Robot Learning
Multiple Subjects
Machine Learning Method, Machine Learning Methods
Case Study, Case Studies
Free Text
Cold War
Caesarean Section
Computational Study, Computational Studies, Computing Studies, Computer Study
Medical Knowledge
Project Report
Cognitive Science, Cognitive Sciences
Cesarean Deliveries, Cesarean Delivery
Rapidly Growing Field
Research Topics
Recent Advances
Pa School
Tour Guide
Neural Networks, Neural Network
Longer Version
Computer Learning, Computational Learning
Reinforcement Learning
Self Improving
Prospective Student
Robotic Control, Robot Control
Different Learning
International Edit
Texas Press
Learning State
Different Languages
Challenge Problems
Carnegie Mellon
Distributed Environment, Distributed Environments
New Thinking
Autonomous Agents, Autonomous Agent
Human Learning
Planetary Exploration
Autonomous Robots, Autonomous Robot, Autonomous Robotics
Knowledge Acquisition
Comparative Analysis
Second International
Explicit Justifications
Expert Knowledge
Preliminary Version
Manipulation Strategies
Earlier Version
Computer Sciences Department, Computer Science Department, Computer Science Departments
Artificial Intelligence Systems
Mechanical Design, Mechanism Design
Computer Science Research
Space Station
Integrity Constraints
Robot Navigation
Mobile Robots, Mobile Robot, Mobile Robotics
Robotic Exploration, Robot Exploration
Expert Systems, Expert System
Human Factors, Human Factor
Nasa Ames Research Center
Database Technologies
Slightly Modified Version
Learning Problem
Solution Paths
Digital Circuits
Learning Generalizations
Concept Learning
Computer Programming, Computer Program
Description Languages
Cambridge Ma
Refining Problem
Learning Algorithm, Learning Algorithms
Learning Systems
List of Publications (438)
In 2016
438
The Semantics of Adjective Noun Phrases in the Human Brain. A Fyshe, G Sudre, L Wehbe, N Rafidi, TM Mitchell bioRxiv, 089615, 2016.
Found on Publication Page
437
A Probabilistic Generative Grammar for Semantic Parsing. A Saparov, TM Mitchell arXiv preprint arXiv:1606.06361, 2016.
Found on Publication Page
436
TurboSMT: Parallel coupled sparse matrixTensor factorizations and applications. EE Papalexakis, TM Mitchell, ND Sidiropoulos, C Faloutsos, PP Talukdar, ... Statistical Analysis and Data Mining: The ASA Data Science Journal 9 (4 ..., 2016.
Found on Publication Page
435
On becoming reactive. J Blythe, TM Mitchell Proceedings of the Sixth International Machine Learning Workshop, 255-259, 2016.
Found on Publication Page
434
Estimating accuracy from unlabeled data: A bayesian approach. EA Platanios, A Dubey, T Mitchell, CS CMU Proceedings of The 33rd International Conference on Machine Learning, 1416-1425, 2016.
Found on Publication Page
433
Instructable intelligent personal agent. A Azaria, J Krishnamurthy, TM Mitchell Proc. The 30th AAAI Conference on Artificial Intelligence (AAAI) 4, 2016.
Found on Publication Page
432
EXPERIMENTS IN ROBOT LEARNING!. MTMAD Christiansen, TM Mitchell Machine Learning Proceedings 1989, 141, 2016.
Found on Publication Page
In 2015
429
AskWorld: budget-sensitive query evaluation for knowledge-on-demand. M Samadi, P Talukdar, M Veloso, T Mitchell Proceedings of the 24th International Conference on Artificial Intelligence ..., 2015.
Found on Publication Page
428
Principled neuro-functional connectivity discovery. K Huang, ND Sidiropoulos, EE Papalexakis, C Faloutsos, PP Talukdar, ... SIAM SDM, 2015.
Found on Publication Page
427
A knowledge-intensive model for prepositional phrase attachment. N Nakashole, TM Mitchell Proceedings of the 53rd Annual Meeting of the Association for Computational ..., 2015.
Found on Publication Page
426
Inferring interpersonal relations in narrative summaries. S Srivastava, S Chaturvedi, T Mitchell arXiv preprint arXiv:1512.00112, 2015.
Found on Publication Page
425
Combining vector space embeddings with symbolic logical inference over open-domain text. M Gardner, P Talukdar, T Mitchell 2015 AAAI Spring Symposium Series 6, 1, 2015.
Found on Publication Page
424
Sense discovery via co-clustering on images and text. X Chen, A Ritter, A Gupta, T Mitchell 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5298 ..., 2015.
Found on Publication Page
423
Machine learning: Trends, perspectives, and prospects. MI Jordan, TM Mitchell Science 349 (6245), 255-260, 2015.
Found on Publication Page
421
Translation invariant word embeddings. M Gardner, K Huang, E Papalexakis, X Fu, P Talukdar, C Faloutsos, ... Proc. of EMNLP, 2015.
Found on Publication Page
420
Learning a compositional semantics for Freebase with an open predicate vocabulary. J Krishnamurthy, TM Mitchell Transactions of the Association for Computational Linguistics 3, 257-270, 2015.
Found on Publication Page
419
Efficient and expressive knowledge base completion using subgraph feature extraction. M Gardner, T Mitchell Proceedings of the 2015 Conference on Empirical Methods in Natural Language ..., 2015.
Found on Publication Page
418
Weakly supervised extraction of computer security events from twitter. A Ritter, E Wright, W Casey, T Mitchell Proceedings of the 24th International Conference on World Wide Web, 896-905, 2015.
Found on Publication Page
417
A compositional and interpretable semantic space. A Fyshe, L Wehbe, PP Talukdar, B Murphy, TM Mitchell Proceedings of the NAACL-HLT, Denver, USA, 2015.
Found on Publication Page
In 2014
416
Turbo-SMT: Accelerating Coupled Sparse Matrix-Tensor Factorizations by 200x. EE Papalexakis, C Faloutsos, TM Mitchell, PP Talukdar, ND Sidiropoulos, ... SDM, 118-126, 2014.
Found on Publication Page
415
Good-Enough Brain Model: Challenges, Algorithms and Discoveries in Multi-Subject Experiments. E Evangelos, A Fyshe, ND Sidiropoulos, PP Talukdar, TM Mitchell, ... .
Found on Publication Page
413
Explanation based learning: A comparison of symbolic and neural network approaches. TM Mitchell, S Thrun Proceedings of the Tenth International Conference on Machine Learning, 197-204, 2014.
Found on Publication Page
412
Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses. L Wehbe, B Murphy, P Talukdar, A Fyshe, A Ramdas, T Mitchell PloS one 9 (11), e112575, 2014.
Found on Publication Page
411
Incorporating vector space similarity in random walk inference over knowledge bases. M Gardner, PP Talukdar, J Krishnamurthy, T Mitchell .
Found on Publication Page
410
CTPs: Contextual Temporal Profiles for Time Scoping Facts using State Change Detection. DT Wijaya, N Nakashole, TM Mitchell EMNLP, 1930-1936, 2014.
Found on Publication Page
409
Never Ending Language Learning. T Mitchell, E Fredkin Big Data (Big Data), 2014 IEEE International Conference on, 1-1, 2014.
Found on Publication Page
408
Mining and organizing a resource of state-changing verbs. DT Wijaya, N Nakashole, TM Mitchell Proceedings of the Joint Workshop on Automatic Knowledge Base Construction ..., 2014.
Found on Publication Page
407
Micro reading with priors: Towards second generation machine readers. N Nakashole, TM Mitchell AKBC at NIPS, 2014.
Found on Publication Page
405
Assuming facts are expressed more than once. J Betteridge, A Ritter, T Mitchell, ADF Clarke, M Elsner, H Rohde, ... .
Found on Publication Page
404
Machine learning: an artificial intelligence approach. Y Kodratoff, RS Michalski Morgan Kaufmann, 2014.
Found on Publication Page
403
Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing. J Kujala, G Sudre, J Vartiainen, M Liljestrm, T Mitchell, R Salmelin NeuroImage 92, 207-216, 2014.
Found on Publication Page
402
Efficient inference and learning in a large knowledge base: Reasoning with extracted information using a locally groundable first-order probabilistic logic. WY Wang, K Mazaitis, N Lao, T Mitchell, WW Cohen arXiv preprint arXiv:1404.3301, 2014.
Found on Publication Page
400
Aligning context-based statistical models of language with brain activity during reading. L Wehbe, A Vaswani, K Knight, TM Mitchell EMNLP, 233-243, 2014.
Found on Publication Page
399
Language-Aware Truth Assessment of Fact Candidates. N Nakashole, TM Mitchell ACL (1), 1009-1019, 2014.
Found on Publication Page
398
Good-Enough Brain Model: Challenges, Algorithms, and Discoveries in Multisubject Experiments. EE Papalexakis, A Fyshe, ND Sidiropoulos, PP Talukdar, TM Mitchell, ... Big Data 2 (4), 216-229, 2014.
Found on Publication Page
396
Joint Syntactic and Semantic Parsing with Combinatory Categorial Grammar. J Krishnamurthy, TM Mitchell ACL (1), 1188-1198, 2014.
Found on Publication Page
395
Interpretable semantic vectors from a joint model of brain-and text-based meaning. A Fyshe, PP Talukdar, B Murphy, TM Mitchell Proceedings of the conference. Association for Computational Linguistics ..., 2014.
Found on Publication Page
394
Identifying autism from neural representations of social interactions: Neurocognitive markers of autism. MA Just, VL Cherkassky, A Buchweitz, TA Keller, TM Mitchell PloS one 9 (12), e113879, 2014.
Found on Publication Page
In 2013
393
Vector space semantic parsing: A framework for compositional vector space models. J Krishnamurthy, T Mitchell .
Found on Publication Page
392
Pidgin: ontology alignment using web text as interlingua. D Wijaya, PP Talukdar, T Mitchell Proceedings of the 22nd ACM international conference on Information ..., 2013.
Found on Publication Page
391
Office Automation Systems that are Programmed by. S Bocionek, TM Mitchell InformatikWirtschaftGesellschaft: 23. GIJahrestagung, Dresden, 27 ..., 2013.
Found on Publication Page
390
Improving learning and inference in a large knowledge-base using latent syntactic cues. M Gardner, PP Talukdar, B Kisiel, T Mitchell .
Found on Publication Page
389
CMUML system for KBP 2013 slot filling. B Kisiel, J Betteridge, M Gardner, J Krishnamurthy, N Nakashole, ... Proc. TAC 2013 Workshop, 2013.
Found on Publication Page
388
Machine learning: An artificial intelligence approach. Springer Science & Business Media, 2013.
Found on Publication Page
387
Scoup-SMT: Scalable coupled sparse matrix-tensor factorization. EE Papalexakis, TM Mitchell, ND Sidiropoulos, C Faloutsos, PP Talukdar, ... arXiv preprint arXiv:1302.7043, 2013.
Found on Publication Page
386
Documents and Dependencies: an Exploration of Vector Space Models for Semantic Composition. A Fyshe, B Murphy, PP Talukdar, TM Mitchell CoNLL, 84-93, 2013.
Found on Publication Page
In 2012
385
Exploring commonalities across participants in the neural representation of objects. SV Shinkareva, VL Malave, MA Just, TM Mitchell Human brain mapping 33 (6), 1375-1383, 2012.
Found on Publication Page
384
Is that a tool? ERP indexes of perceived affordance and object perceptual awareness. AM Proverbio, R Azzari, R Adorni International Journal of Psychophysiology 85 (3), 330-331, 2012.
Found on Publication Page
383
Learning effective and interpretable semantic models using non-negative sparse embedding. B Murphy, PP Talukdar, T Mitchell Association for Computational Linguistics, 2012.
Found on Publication Page
382
Identifying bilingual semantic neural representations across languages. A Buchweitz, SV Shinkareva, RA Mason, TM Mitchell, MA Just Brain and language 120 (3), 282-289, 2012.
Found on Publication Page
381
Acquiring temporal constraints between relations. PP Talukdar, D Wijaya, T Mitchell Proceedings of the 21st ACM international conference on Information and ..., 2012.
Found on Publication Page
380
Selecting corpus-semantic models for neurolinguistic decoding. B Murphy, P Talukdar, T Mitchell Proceedings of the First Joint Conference on Lexical and Computational ..., 2012.
Found on Publication Page
379
Tracking neural coding of perceptual and semantic features of concrete nouns. G Sudre, D Pomerleau, M Palatucci, L Wehbe, A Fyshe, R Salmelin, ... NeuroImage 62 (1), 451-463, 2012.
Found on Publication Page
378
Comparing Abstract and Concrete Conceptual Representations using Neurosemantic Decoding. B Murphy, P Talukdar, T Mitchell NAACL Workshop on Cognitive Modelling and Computational Linguistics, 2012.
Found on Publication Page
377
Decoding word semantics from magnetoencephalography time series transformations. A Fyshe, G Sudre, L Wehbe, B Murphy, T Mitchell 2nd NIPS Workshop on Machine Learning and Interpretation in NeuroImaging (MLINI), 2012.
Found on Publication Page
376
Coupled temporal scoping of relational facts. PP Talukdar, D Wijaya, T Mitchell Proceedings of the fifth ACM international conference on Web search and data ..., 2012.
Found on Publication Page
375
Weakly supervised training of semantic parsers. J Krishnamurthy, TM Mitchell Proceedings of the 2012 Joint Conference on Empirical Methods in Natural ..., 2012.
Found on Publication Page
374
Hierarchical Latent Dictionaries for Models of Brain Activation. A Fyshe, EB Fox, DB Dunson, TM Mitchell AISTATS, 409-421, 2012.
Found on Publication Page
In 2011
373
Which noun phrases denote which concepts?. J Krishnamurthy, TM Mitchell Proceedings of the 49th Annual Meeting of the Association for Computational ..., 2011.
Found on Publication Page
372
Supervision Reduction by Encoding Extra Information about Models, Features and Labels. Y Zhang, G Gordon, T Mitchell .
Found on Publication Page
371
Learning with Sparsity: Structures, Optimization and Applications. T Mitchell Department of Statistics, Stanford University, 2011.
Found on Publication Page
370
Quantitative modeling of the neural representation of objects: How semantic feature norms can account for fMRI activation. KK Chang, T Mitchell, MA Just NeuroImage 56 (2), 716-727, 2011.
Found on Publication Page
369
From journal articles to computational models: a new automated tool. TM Mitchell Nature methods 8 (8), 627, 2011.
Found on Publication Page
368
Random walk inference and learning in a large scale knowledge base. N Lao, T Mitchell, WW Cohen Proceedings of the Conference on Empirical Methods in Natural Language ..., 2011.
Found on Publication Page
367
Commonality of neural representations of words and pictures. SV Shinkareva, VL Malave, RA Mason, TM Mitchell, MA Just Neuroimage 54 (3), 2418-2425, 2011.
Found on Publication Page
366
Discovering relations between noun categories. TP Mohamed, ER Hruschka Jr, TM Mitchell Proceedings of the Conference on Empirical Methods in Natural Language ..., 2011.
Found on Publication Page
365
Human computation for attribute and attribute value acquisition. E Law, B Settles, A Snook, H Surana, L Von Ahn, T Mitchell Proceedings of the First Workshop on Fine-Grained Visual Categorization (FGVC) 2, 2011.
Found on Publication Page
In 2010
364
Learning to tag from open vocabulary labels. E Law, B Settles, T Mitchell Joint European Conference on Machine Learning and Knowledge Discovery in ..., 2010.
Found on Publication Page
363
From Data to Knowledge to Action: Enabling Advanced Intelligence and Decision-Making for Americas Security. RE Bryant, JG Carbonell, T Mitchell Computing Community Consortium, Version 6, 2010.
Found on Publication Page
362
A neurosemantic theory of concrete noun representation based on the underlying brain codes. MA Just, VL Cherkassky, S Aryal, TM Mitchell PloS one 5 (1), e8622, 2010.
Found on Publication Page
361
Coupled semi-supervised learning for information extraction. A Carlson, J Betteridge, RC Wang, ER Hruschka Jr, TM Mitchell Proceedings of the third ACM international conference on Web search and data ..., 2010.
Found on Publication Page
360
Toward an Architecture for Never-Ending Language Learning. A Carlson, J Betteridge, B Kisiel, B Settles, ER Hruschka Jr, TM Mitchell AAAI 5, 3, 2010.
Found on Publication Page
359
From Data to Knowledge to Action: A Global Enabler for the 21 st Century. E Horvitz, T Mitchell Computing 1, 2010.
Found on Publication Page
357
"Coupled Semi-Supervised Learning for Information Extraction," Andrew Carlson, Justin Betteridge, Richard C. Wang, Estevam R. Hruschka Jr. and Tom M. Mitchell. Proceedings of the Third ACM International Conference on Web Search and Data Mining (WSDM), Feb. 2010.
Found on CV
In 2009
356
"Machine learning classifiers and fMRI: a tutorial overview," Pereira F., Mitchell T., Botvinick M., NeuroImage, Volume 45, Issue 1, Pages S199-S209, March 2009.
Found on CV
355
"Integrating Multiple-Study Multiple-Subject fMRI Datasets Using Canonical Correlation Analysis", I. Rustandi, M.A. Just, T.M. Mitchell. Proceedings of the MICCAI 2009 Workshop: Statistical modeling and detection issues in intra- and inter-subject functional MRI data analysis, September 2009.
Found on CV
354
"Modeling fMRI Data Generated by Overlapping Cognitive Processes with Unknown Onsets Using Hidden Process Models," R.A. Hutchinson, R.S. Niculescu, T.A. Keller, I. Rustandi, T.M. Mitchell, NeuroImage (2009), doi: 10.1016/j.neuroimage.2009.01.025
Found on CV
353
Toward Never Ending Language Learning. J Betteridge, A Carlson, SA Hong, ER Hruschka Jr, ELM Law, TM Mitchell, ... AAAI Spring Symposium: Learning by Reading and Learning to Read, 1-2, 2009.
Found on Publication Page
352
Integrating multiple-study multiple-subject fMRI datasets using canonical correlation analysis. I Rustandi, MA Just, T Mitchell Proceedings of the MICCAI 2009 Workshop: Statistical modeling and detection ..., 2009.
Found on Publication Page
351
"Mining Our Reality," Tom M. Mitchell, Perspective in Science, 326, DOI:10.1126/science.1174459, December 2009.
Found on CV
350
Modeling fMRI data generated by overlapping cognitive processes with unknown onsets using Hidden Process Models. RA Hutchinson, RS Niculescu, TA Keller, I Rustandi, TM Mitchell NeuroImage 46 (1), 87-104, 2009.
Found on Publication Page
349
Toward Mixed-Initiative Email Clustering. Y Huang, TM Mitchell AAAI Spring Symposium: Agents that Learn from Human Teachers, 71-78, 2009.
Found on Publication Page
348
Zero-shot learning with semantic output codes. M Palatucci, D Pomerleau, GE Hinton, TM Mitchell Advances in neural information processing systems, 1410-1418, 2009.
Found on Publication Page
347
Machine learning classifiers and fMRI: a tutorial overview. F Pereira, T Mitchell, M Botvinick Neuroimage 45 (1), S199-S209, 2009.
Found on Publication Page
346
"Coupling Semi-Supervised Learning of Categories and Relations," A. Carlson, J. Betteridge, E. R. Hruschka Jr. and T. M. Mitchell. NAACL HLT 2009 Workshop on Semi-supervised Learning for Natural Language Processing, June 2009.
Found on CV
345
Populating the semantic web by macro-reading internet text. T Mitchell, J Betteridge, A Carlson, E Hruschka, R Wang The Semantic Web-ISWC 2009, 998-1002, 2009.
Found on Publication Page
343
eAssessment for learning? The potential of shortanswer freetext questions with tailored feedback. S Jordan, T Mitchell British Journal of Educational Technology 40 (2), 371-385, 2009.
Found on Publication Page
342
Quantitative modeling of the neural representation of adjective-noun phrases to account for fMRI activation. KK Chang, VL Cherkassky, TM Mitchell, MA Just Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL ..., 2009.
Found on Publication Page
341
"Zero-Shot Learning with Semantic Output Codes", M. Palatucci, D. Pomerleau, G. Hinton, T. Mitchell, Neural Information Processing Systems (NIPS), 2009.
Found on CV
340
Coupling semi-supervised learning of categories and relations. A Carlson, J Betteridge, ER Hruschka Jr, TM Mitchell Proceedings of the NAACL HLT 2009 Workshop on Semi-supervised Learning for ..., 2009.
Found on Publication Page
339
A combined expression-interaction model for inferring the temporal activity of transcription factors. Y Shi, M Klutstein, I Simon, T Mitchell, Z Bar-Joseph Journal of Computational Biology 16 (8), 1035-1049, 2009.
Found on Publication Page
338
"Populating the Semantic Web by Macro-Reading Internet Text", Tom M. Mitchell, Justin Betteridge, Andrew Carlson, Estevam Hruschka, and Richard Wang, Invited paper, Proceedings of the 8th International Semantic Web Conference (ISWC 2009), October 2009.
Found on CV
337
Search war: a game for improving web search. E Law, L von Ahn, T Mitchell Proceedings of the acm sigkdd workshop on human computation, 31-31, 2009.
Found on Publication Page
In 2008
336
"Combining Labeled and Unlabeled Data with Co-Training," A. Blum and T. Mitchell, Proceedings of the 1998 Conference on Computational Learning Theory, July 1998. Received 10-Year Best Paper Award at ICML/COLT in 2008.
Found on CV
335
Computational models of neural representations in the human brain. TM Mitchell International Conference on Discovery Science, 26-27, 2008.
Found on Publication Page
334
The Spy who Tried to Stop a War: Katharine Gun and the Secret Plot to Sanction the Iraq Invasion. M Mitchell, T Mitchell PoliPointPress, 2008.
Found on Publication Page
333
"Discovering a Semantic Basis of Neural Activity Using Simultaneous Sparse Approximation," M. Palatucci, T.M. Mitchell, and H. Liu International Conference on Machine Learning (ICML)-Sparse Optimization and Variable Selection Workshop, 2008.
Found on Publication Text
332
Using fMRI brain activation to identify cognitive states associated with perception of tools and dwellings. SV Shinkareva, RA Mason, VL Malave, W Wang, TM Mitchell, MA Just PLoS One 3 (1), e1394, 2008.
Found on Publication Page
331
Predicting human brain activity associated with the meanings of nouns. TM Mitchell, SV Shinkareva, A Carlson, KM Chang, VL Malave, RA Mason, ... science 320 (5880), 1191-1195, 2008.
Found on Publication Page
330
"Computational Models of Neural Representations in the Human Brain," (extended abstract) T.M. Mitchell, DS 2008, Lecture Notes in Artificial Intelligence 5255, J.-F. Boulicaut, M.R. Berthold, and T. Horvarth (Eds.), Springer-Verlag Berlin Heidelberg, pp. 26 27, 2008.
Found on CV
329
Enhanced Messaging Workshop, AAAI 2008, Chicago, IL, July 2008
Found on CV
328
"Predicting Human Brain Activity Associated with the Meanings of Nouns," T. M. Mitchell, S. V. Shinkareva, A. Carlson, K. Chang, V. L. Malave, R. A. Mason, M. A. Just, Science, vol. 320, May 30, 2008.
Found on CV
327
A combined expression-interaction model for inferring the temporal activity of transcription factors. Y Shi, I Simon, T Mitchell, Z Bar-Joseph Annual International Conference on Research in Computational Molecular ..., 2008.
Found on Publication Page
326
Exploring hierarchical user feedback in email clustering. Y Huang, TM Mitchell EMAIL08: Proceedings of the Workshop on Enhanced Messaging-AAAI, 36-41, 2008.
Found on Publication Page
325
The Real McCain: Why Conservatives Don't Trust Him, and why Independents Shouldn't. C Schecter PoliPointPress, 2008.
Found on Publication Page
324
"Using fMRI Brain Activation to Identify Cognitive States Associated with Perception of Tools and Dwellings," S.V. Shinkareva, R.A. Mason, V.L. Malave, W. Wang, T. M. Mitchell, and M. A. Just, PLoS ONE 3(1): e1394. doi:10.1371/journal.pone.0001394, January 2, 2008.
Found on CV
323
"A Combined Expression-Interaction Model for Inferring the Temporal Activity of Transcription Factors," Y. Shi, I. Simon, T. Mitchell1 and Z. Bar-Joseph, Proceedings of The 12th Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2008.
Found on CV
322
"Discovering a Semantic Basis of Neural Activity Using Simultaneous Sparse Approximation," M. Palatucci, T.M. Mitchell, and H. Liu International Conference on Machine Learning (ICML - Sparse Optimization and Variable Selection Workshop), July, 2008.
Found on CV
321
Data analysis project: Leveraging massive textual corpora using n-gram statistics. A Carlson, TM Mitchell, I Fette CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE, 2008.
Found on Publication Page
In 2007
320
Inferring pairwise regulatory relationships from multiple time series datasets. Y Shi, T Mitchell, Z Bar-Joseph Bioinformatics 23 (6), 755-763, 2007.
Found on Publication Page
319
In honor of Marvin Minsky's contributions on his 80th birthday. D Hillis, J McCarthy, TM Mitchell, ET Mueller, D Riecken, A Sloman, ... AI Magazine 28 (4), 103, 2007.
Found on Publication Page
318
Feature selection for grasp recognition from optical markers. LY Chang, NS Pollard, TM Mitchell, EP Xing 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems ..., 2007.
Found on Publication Page
317
Framework for mixed-initiative clustering. Y Huang, T Mitchell North East Student Colloquium on Artificial Intelligence (NESCAI 2007), 2007.
Found on Publication Page
316
"Feature Selection for Grasp Recognition from Optical Markers," L.Y. Chang, N. Pollard, T. Mitchell, and E.P. Xing, Proceedings of the 2007 IEEE/RSJ Intl. Conference on Intelligent Robots and Systems (IROS 2007), pp. 2944-2950, October, 2007.
Found on CV
315
"Classification in Very High Dimensional Problems with Handfuls of Examples," M. Palatucci and T. Mitchell, Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), Springer- Verlag, September, 2007
Found on CV
314
"Inferring Gene Regulatory Relationships from Multiple Time Series Datasets'" Y. Shi, T. Mitchell and Z. Bar-Joseph , Bioinformatics, 23(6), pp. 755-763, 2007.
Found on CV
313
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints. RS Niculescu, TM Mitchell, RB Rao IJCAI, 155-160, 2007.
Found on Publication Page
312
"Continuous hidden process model for time series expression experiments," Y. Shi, M. Klustein, I. Simon, T. Mitchell, and Z. Bar-Joseph, Bioinformatics (Proceedings of ISMB 2007), 23(13), pp i459-i467, 2007.
Found on CV
311
Classification in very high dimensional problems with handfuls of examples. M Palatucci, TM Mitchell European Conference on Principles of Data Mining and Knowledge Discovery ..., 2007.
Found on Publication Page
310
Continuous hidden process model for time series expression experiments. Y Shi, M Klustein, I Simon, T Mitchell, Z Bar-Joseph Bioinformatics 23 (13), i459-i467, 2007.
Found on Publication Page
In 2006
309
Hidden process models. RA Hutchinson, TM Mitchell, I Rustandi Proceedings of the 23rd international conference on Machine learning, 433-440, 2006.
Found on Publication Page
308
"Decoding of Semantic Category Information from Single Trial fMRI Activation in Response to Word Stimuli", Using Searchlight Voxel Selection ," F. Pereira, R. Mason, M. Just, T. Mitchell, N. Kriegeskorte, 12th Conference on Human Brain Mapping, June, 2006.
Found on CV
307
Exploring predictive and reproducible modeling with the singlesubject FIAC dataset. X Chen, F Pereira, W Lee, S Strother, T Mitchell Human Brain Mapping 27 (5), 452-461, 2006.
Found on Publication Page
306
Extracting Knowledge about Users Activities from Raw Workstation. TM Mitchell, SH Wang, Y Huang, A Cheyer AAAI 2006 1, 181, 2006.
Found on Publication Page
305
"Extracting Knowledge about Users' Activities from Raw Workstation Contents," T. Mitchell, S. Wang, Y. Huang, and A. Cheyer, in Proceedings of the AAAI Conference, July 2006.
Found on CV
304
Decoding of semantic category information from single trial fMRI activation in response to word stimuli, using searchlight voxel selection. F Pereira, R Mason, M Just, T Mitchell, N Kriegeskorte 12th Conference on Human Brain Mapping, 2006.
Found on Publication Page
303
Semi-Supervised Learning. K Nigam, A McCallum, T Mitchell MIT Press, Boston, chapter Semi-supervised Text Classification Using EM, 2006.
Found on Publication Page
302
Semi-supervised text classification using EM. K Nigam, A McCallum, T Mitchell Semi-Supervised Learning, 33-56, 2006.
Found on Publication Page
301
"Classifying cognitive states associated with reading single words and two-word sentences," Svetlana V. Shinkareva, Robert A. Mason, Vicente L. Malave, Tom M. Mitchell, Marcel A. Just. 12th Conference on Human Brain Mapping, June, 2006.
Found on Publication Text
299
The discipline of machine learning. TM Mitchell Carnegie Mellon University, School of Computer Science, Machine Learning ..., 2006.
Found on Publication Page
298
"Semi-Supervised Text Classification Using EM," K. Nigam, A. McCallum, and T. Mitchell, in Semi-Supervised Learning, Olivier Chapelle, Bernhard Sch olkopf, and Alexander Zien (eds.), MIT Press, 2006.
Found on CV
297
"Exploring predictive and reproducible modeling with the single-subject FIAC data set," X. Chen, F. Pereira, W. Lee, S. Strother, T. Mitchell, Human Brain Mapping, 2006.
Found on CV
296
"Hidden Process Models," R. Hutchinson, T. Mitchell, I. Rustandi, in Proceedings of the International Conference on Machine Learning, Pittsburgh, PA, June 2006.
Found on CV
295
Bayesian network learning with parameter constraints. RS Niculescu, TM Mitchell, RB Rao Journal of Machine Learning Research 7 (Jul), 1357-1383, 2006.
Found on Publication Page
294
Text clustering with extended user feedback. Y Huang, TM Mitchell Proceedings of the 29th annual international ACM SIGIR conference on ..., 2006.
Found on Publication Page
293
"Bayesian Network Learning with Parameter Constraints," R.S. Niculescu, T.M. Mitchell, R.B. Rao, Journal of Machine Learning Research, 7, pp. 1357-1383, July 2006.
Found on CV
292
"Classifying cognitive states associated with reading single words and two-word sentences," Svetlana V. Shinkareva, Robert A. Mason, Vicente L. Malave, Tom M. Mitchell, Marcel A. Just. 12th Conference on Human Brain Mapping, June, 2006.
Found on CV
291
"Text Clustering with Extended User Feedback," Y. Huang and T. Mitchell, Proceedings of SIGIR 2006, August, 2006.
Found on CV
In 2005
290
Predicting dire outcomes of patients with community acquired pneumonia. GF Cooper, V Abraham, CF Aliferis, JM Aronis, BG Buchanan, R Caruana, ... Journal of Biomedical Informatics 38 (5), 347-366, 2005.
Found on Publication Page
289
Cognitive styles and adaptive web-based learning. TJF Mitchell, SY Chen, RD Macredie Psychology of Education Review 29 (1), 34-42, 2005.
Found on Publication Page
288
"Learning to Identify Overlapping and Hidden Cognitive Processes from fMRI Data," R. Hutchinson, T.M. Mitchell, I. Rustandi, 11th Conference on Human Brain Mapping, June, 2005.
Found on CV
287
Method for learning and combining global and local regularities for information extraction and classification. DW Quass, TM Mitchell, AK McCallum, W Cohen US Patent 6,892,189, 2005.
Found on Publication Page
285
Cognitive Styles and Adaptive Web-based Learning. RD Macredie, TJF Mitchell, SY Chen School of Information Systems, Computing and Mathematics;, 2005.
Found on Publication Page
284
The relationship between web enjoyment and student perceptions and learning using a webbased tutorial. TJF Mitchell, SY Chen, RD Macredie Learning, Media and Technology 30 (1), 27-40, 2005.
Found on Publication Page
283
Learning to identify overlapping and hidden cognitive processes from fMRI data. R Hutchinson, TM Mitchell, I Rustandi 11th Conference on Human Brain Mapping, 2005.
Found on Publication Page
281
Hypermedia learning and prior knowledge: domain expertise vs. system expertise. TJF Mitchell, SY Chen, RD Macredie Journal of Computer Assisted Learning 21 (1), 53-64, 2005.
Found on Publication Page
280
"Predicting Dire Outcomes of Patients with Community Acquired Pneumonia," G.F.Cooper, V. Abraham, C. F. Aliferis, J M. Aronis, B. G. Buchanan, R. Caruana, M. J. Fine, J. E. Janosky, G. Livingston, T. Mitchell, S. Montik, and P. Spirtes, Journal of Biomedical Informatics, 38, 2005, pp. 347-366.
Found on CV
279
Exploiting Parameter Related Domain Knowledge for Learning in Graphical Models. RS Niculescu, TM Mitchell, RB Rao SDM, 310-321, 2005.
Found on Publication Page
278
"Learning Topic-Based Mixture Models for Factored Classification," Q. Chen and T. M. Mitchell, Proceedings of the International Conference on Intelligent Agents, Web Technologies and Internet Commerce - IAWTIC'2005, IEEE Computer Society, M. Mohammadian (ed.), Vienna, Austria, November 2005, pp. 1114--1120.
Found on CV
In 2004
276
"Learning to Decode Cognitive States from Brain Images," T.M. Mitchell, R. Hutchinson, R.S. Niculescu, F.Pereira, X. Wang, M. Just, and S. Newman, Machine Learning, Vol. 57, Issue 1-2, pp. 145-175, October, 2004.
Found on CV
275
Adapting hypermedia to cognitive styles: is it necessary. T Mitchell, SY Chen, R Macredie Proc. of Workshop on Individual Differences in Adaptive Hypermedia at the ..., 2004.
Found on Publication Page
274
Inferring Ongoing Activities of Workstation Users by Clustering Email. Y Huang, D Govindaraju, TM Mitchell, VR de Carvalho, WW Cohen CEAS, 2004.
Found on Publication Page
273
Learning to Classify Email into``Speech Acts''. WW Cohen, VR Carvalho, TM Mitchell EMNLP, 309-316, 2004.
Found on Publication Page
272
Learning to decode cognitive states from brain images. TM Mitchell, R Hutchinson, RS Niculescu, F Pereira, X Wang, M Just, ... Machine Learning 57 (1-2), 145-175, 2004.
Found on Publication Page
271
Detecting significant multidimensional spatial clusters. DB Neill, AW Moore, F Pereira, TM Mitchell Advances in Neural Information Processing Systems, 969-976, 2004.
Found on Publication Page
270
"Learning to Classify Email into Speech Acts," W. Cohen, Vi. R. Carvalho, and T. M. Mitchell, Proceedings of the Conference on Empirical Methods in Natural Language Processing, Barcelona, July 2004.
Found on CV
269
"Detecting Significant Multidimensional Spatial Clusters," D.Neill, A. Moore, F. Pereira, T.M. Mitchell, Neural Information Processing Systems, December, 2004.
Found on CV
268
"Inferring Ongoing Activities of Workstation Users by Clustering Email," Y. Huang, D. Govindaraju, T. M. Mitchell, First Conference on Email and Anti-Spam, CEAS2004, Mountain View, CA, July 2004.
Found on CV
In 2003
267
Classifying instantaneous cognitive states from fMRI data. TM Mitchell, R Hutchinson, MA Just, RS Niculescu, F Pereira, X Wang American medical informatics association annual symposium, 2003.
Found on Publication Page
266
Training fMRI classifiers to discriminate cognitive states across multiple subjects. X Wang, RA Hutchinson, TM Mitchell Advances in neural information processing systems, None, 2003.
Found on Publication Page
265
Computer based testing of medical knowledge. T Mitchell, N Aldridge, W Williamson, P Broomhead Proceedings of the 7th computer assisted assessment conference, 249-267, 2003.
Found on Publication Page
264
In Memoriam: Charles Rosen, Norman Nielsen, and Saul Amarel. PE Hart, NJ Nilsson, R Perrault, T Mitchell, CA Kulikowski, DB Leake AI Magazine 24 (1), 6, 2003.
Found on Publication Page
263
Artificial intelligence and human brain imaging. TM Mitchell Conference of the Canadian Society for Computational Studies of Intelligence ..., 2003.
Found on Publication Page
262
Computerised marking of free text responses. T Mitchell, N Aldridge PASS-IT Project Report for the SQA (Scottish Qualifications Authority), 2003.
Found on Publication Page
261
"Classifying Instantaneous Cognitive States from fMRI Data," T. Mitchell, R. Hutchinson, M. Just, R.S. Niculescu, F. Pereira, X. Wang, American Medical Informatics Association Annual Symposium, Washington D.C., November 2003. received 'Best Foundational Paper' award.
Found on CV
260
Active learning for information extraction with multiple view feature sets. R Jones, R Ghani, T Mitchell, E Riloff Proc. of Adaptive Text Extraction and Mining, EMCL/PKDD-03, Cavtat-Dubrovnik ..., 2003.
Found on Publication Page
259
Computerised marking of short-answer free-text responses. T Mitchell, N Aldridge, P Broomhead Manchester IAEA conference, 2003.
Found on Publication Page
258
Using machine learning to detect cognitive states across multiple subjects. X Wang, TM Mitchell, R Hutchinson CALD KDD project paper, 2003.
Found on Publication Page
257
"Training fMRI Classifiers to Detect Cognitive States across Multiple Human Subjects ," X. Wang, R. Hutchinson, and T. M. Mitchell, Neural Information Processing Systems, Vancouver, December 2003.
Found on CV
In 2002
256
Towards robust computerised marking of free-text responses. T Mitchell, T Russell, P Broomhead, N Aldridge Loughborough University, 2002.
Found on Publication Page
255
The Spy who Seduced America: Lies and Betrayal in the Heat of the Cold War: the Judith Coplon Story. M Mitchell, T Mitchell Invisible Cities Press, 2002.
Found on Publication Page
254
"The Role of Unlabeled Data in Supervised Learning," T. Mitchell, Proceedings of the Sixth International Colloquium on Cognitive Science, San Sebastian, Spain, 1999 (invited paper). Also appears in Language, Knowledge, and Representation, J.M. Larrazabel and L.A. Perez Miranda (eds.), Klwer Academic Publishers, pp. 97-104, (2002).
Found on CV
253
Detecting cognitive states using machine learning. X Wang, T Mitchell Iterim working paperWhiteld ML, Sherlock G, Saldanha A, Murray JI, Ball CA ..., 2002.
Found on Publication Page
252
Machine learning of fMRI virtual sensors of cognitive states. T Mitchell, R Hutchinson, M Just, S Newman, R Niculescu, F Periera, ... The 16th Annual Conference on Neural Information Processing Systems ..., 2002.
Found on Publication Page
In 2001
251
Distinguishing natural language processes on the basis of fMRI-measured brain activation. F Pereira, M Just, T Mitchell European Conference on Principles of Data Mining and Knowledge Discovery ..., 2001.
Found on Publication Page
250
A Case Study in Using Linguistic Phrases for Text Categorization on the WWW. E Riloff, J Frnkranz, T Mitchell AAAI/ICML Work. Learning for Text Categorization, 2001.
Found on Publication Page
249
Extracting targeted data from the web. T Mitchell Proceedings of the seventh ACM SIGKDD international conference on Knowledge ..., 2001.
Found on Publication Page
248
"Distinguishing Natural Language Processes on the Basis of fMRI-measured Brain Activation," F. Pereira, M. Just, T. Mitchell, PKDD 2001, Freiburg, Germany, 2001.
Found on CV
In 2000
247
"Discovering test set regularities in relational domains," S. Slattery and T.M. Mitchell. Proceedings of the 17th International Conference on Machine Learning (ICML-00), pp. 895-902, Morgan Kaufmann, 2000.
Found on CV
246
Discovering test set regularities in relational domains. S Slattery, T Mitchell ICML, 895-902, 2000.
Found on Publication Page
245
Predicting cesarean delivery with decision tree models. CJ Sims, L Meyn, R Caruana, RB Rao, T Mitchell, M Krohn American journal of obstetrics and gynecology 183 (5), 1198-1206, 2000.
Found on Publication Page
244
"Predicting Caesarean Section with Decision Trees," C. Simms, R. Caruana, M.J. Krohn, L. Meyn, T.M. Mitchell, R.B. Rao, and I. Schmeuking, Annual Meeting of the Society of Fetal and Maternal Medicine, February 2000
Found on Publication Text
243
Learning to construct knowledge bases from the World Wide Web. M Craven, D DiPasquo, D Freitag, A McCallum, T Mitchell, K Nigam, ... Artificial intelligence 118 (1), 69-113, 2000.
Found on Publication Page
242
Text classification from labeled and unlabeled documents using EM. K Nigam, AK McCallum, S Thrun, T Mitchell Machine learning 39 (2-3), 103-134, 2000.
Found on Publication Page
241
"Predicting Caesarean Section with Decision Trees," C. Simms, R. Caruana, M.J. Krohn, L. Meyn, T.M. Mitchell, R.B. Rao, and I. Schmeuking, Annual Meeting of the Society of Fetal and Maternal Medicine, February 2000
Found on CV
In 1999
240
Automated Learning and Discovery State-of-the-Art and Research Topics in a Rapidly Growing Field. S Thrun, C Faloutsos, T Mitchell, L Wasserman Ai Magazine 20 (3), 78, 1999.
Found on Publication Page
239
"Text Classification from Labeled and Unlabeled Documents using EM," K. Nigam, Andrew McCallum, Sebastian Thrun and Tom Mitchell. Machine Learning, Kluwer Academic Press, 1999.
Found on CV
238
The role of unlabeled data in supervised learning. T Mitchell Proceedings of the sixth international colloquium on cognitive science, 2-11, 1999.
Found on Publication Page
237
"Machine Learning and Data Mining," T. Mitchell, Communications of the ACM, Vol. 42, No. 11, November 1999.
Found on CV
236
"Learning to Construct Knowledge Bases from the World Wide Web," M. Craven, D. DiPasquo, D. Freitag, A. McCallum, T. Mitchell, K. Nigam, and S. Slattery, Artificial Intelligence, Elsevier, 1999.
Found on CV
In 1998
235
Using EM to classify text from labeled and unlabeled documents. K Nigam, A McCallum, S Thrun, T Mitchell CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE, 1998.
Found on Publication Page
234
"Improving Text Classification by Shrinkage in a Hierarchy of Classes," A. McCallum, R. Rosenfeld, T. Mitchell and A. Ng. Proceedings of the 1998 International Conference on Machine Learning. July 1998.
Found on CV
233
Conditions for the equivalence of hierarchical and non-hierarchical bayesian classifiers. T Mitchell Technical note, 1998.
Found on Publication Page
232
"Learning to Extract Symbolic Knowledge from the World Wide Web," M. Craven, D. DiPasquo, D. Freitag, A. McCallum, T. Mitchell, K. Nigam, and S. Slattery, Proceedings of the 1998 National Conference on Artificial Intelligence, July 1998.
Found on CV
231
A case study in using linguistic phrases for text categorization on the WWW. J Furnkranz, T Mitchell, E Riloff Working Notes of the AAAI/ICML, Workshop on Learning for Text Categorization ..., 1998.
Found on Publication Page
230
Learning to classify text from labeled and unlabeled documents. K Nigam, A McCallum, S Thrun, T Mitchell AAAI/IAAI 792, 1998.
Found on Publication Page
229
Improving Text Classification by Shrinkage in a Hierarchy of Classes. A McCallum, R Rosenfeld, TM Mitchell, AY Ng ICML 98, 359-367, 1998.
Found on Publication Page
228
Learning to extract symbolic knowledge from the World Wide Web. M Craven, A McCallum, D PiPasquo, T Mitchell, D Freitag Carnegie-mellon univ pittsburgh pa school of computer Science, 1998.
Found on Publication Page
227
Combining labeled and unlabeled data with co-training. A Blum, T Mitchell Proceedings of the eleventh annual conference on Computational learning ..., 1998.
Found on Publication Page
226
Automated Learning and Discovery: State-Of-The-Art and Research Topics in a Rapidly Growing Field. S Thrun, C Faloutsos, T Mitchell, L Wasserman AI Magazine, 1998.
Found on Publication Page
224
Report on the CONALD Workshop on Learning from Text and the Web. J Carbonell, M Craven, S Fienberg, T Mitchell, Y Yang Pittsburgh, PA, June, 1998.
Found on Publication Page
223
"Learning to Classify Text from Labeled and Unlabeled Documents," A. McCallum, K. Nigam, S. Thrun, and T. Mitchell, Proceedings of the 1998 National Conference on Artificial Intelligence, July 1998.
Found on CV
In 1997
219
An evaluation of machine-learning methods for predicting pneumonia mortality. GF Cooper, CF Aliferis, R Ambrosino, J Aronis, BG Buchanan, R Caruana, ... Artificial intelligence in medicine 9 (2), 107-138, 1997.
Found on Publication Page
218
"Does Machine Learning Really Work?," T. Mitchell, Invited paper, AI Magazine, Vol. 18, Number 3, AAAI Press, Fall 1997, p.11-20.
Found on CV
216
Machine Learning (McGraw-Hill International Editions Computer Science Series). TM Mitchell McGraw-Hill, 1997.
Found on Publication Page
215
Classification of world wide web documents. CY Quek, T Mitchell Master's thesis, School of Computer Science Carnegie Mellon University, 1997.
Found on Publication Page
213
Data Mining at CALD-CMU: Tools, Experiences and Research Directions. C Faloutsos, G Gibson, T Mitchell, AW Moore, S Thrun afcea, 1997.
Found on Publication Page
212
Machine Learning, Ed. Science/Engineering/Math, Portland, OR. T Mitchell USA: McGraw Hill, 1997.
Found on Publication Page
206
Webwatcher: A tour guide for the world wide web. T Joachims, D Freitag, T Mitchell IJCAI (1), 770-777, 1997.
Found on Publication Page
205
"An Evaluation of Machine-Learning Methods for Predicting Pneumonia Mortality," G. Cooper, C. Aliferis, R. Ambrosino, J. Aronic, B. Buchanan, R. Caruana, M. Fine, C. Glymour, G. Gordon, B. Hanusa, J. Janosky, C. Meek, T. Mitchell, R. Richardson, and P. Spirtes, Artificial Intelligence in Medicine, 1997.
Found on CV
202
Machine learning (mcgraw-hill international edit). T Mitchell McGraw-Hill Education (ISE Editions), 1997.
Found on Publication Page
200
Machine Learning, T.M. Mitchell, McGraw Hill, 1997.
Found on CV
199
"Data Mining at CALD-CMU: Tools, Experiences and Research Directions" C. Faloutsos, G. Gibson, T. Mitchell, A. Moore, S. Thrun, First Federal Data Mining Symposium, Washington, D.C., December 1997.
Found on CV
198
"WebWatcher: A Tour Guide for the World Wide Web," T. Joachims, D. Freitag, and T. Mitchell, Proceedings of the 1997 IJCAI, August 1997.
Found on CV
196
"Learning to Extract Symbolic Knowledge from the World Wide Web," M. Craven, D. Freitag, A. McCallum, T. Mitchell, K. Nigam, C.Y. Quek, Internal Report, January 1997.
Found on CV
194
New Thinking in Design: Designing must take place at the scale of life itself. CT Mitchell Urban Land 56, 28-29, 1997.
Found on Publication Page
In 1996
192
Learning analytically and inductively. TM Mitchell, SB Thrun Mind matters: A tribute to Allen Newell, 85-110, 1996.
Found on Publication Page
191
"Explanation Based Learning for Mobile Robot Perception", J. O'Sullivan, T. Mitchell, and S. Thrun, in Symbolic Visual Learning, Ikeuchi and Veloso (eds.), 1996.
Found on CV
190
"Improving Learning Accuracy in Information Filtering," H.C.M. de Kroon, T.M. Mitchell, and E.J.H. Kerckhoffs, Workshop on ML and HCI affiliated with the 1996 International Conference on Machine Learning, Bari, Italy, July 1996.
Found on CV
189
New thinking in design: conversations on theory and practice. CT Mitchell Van Nostrand Reinhold Company, 1996.
Found on Publication Page
188
Improving learning accuracy in information filtering. H Kroon, EJH Kerckhoffs In International Conference on Machine Learning-Workshop on Machine Learning ..., 1996.
Found on Publication Page
186
Scientific discovery processes in children, adults, and machines. D Klahr Mind Matters: Contributions to Cognitive and Computer Science in Honor of ..., 1996.
Found on Publication Page
184
Using the future to" sort out" the present: Rankprop and multitask learning for medical risk evaluation. R Caruana, S Baluja, T Mitchell Advances in neural information processing systems, 959-965, 1996.
Found on Publication Page
183
Recent Advances in Robot Learning, J. Franklin, T. Mitchell, and S. Thrun (eds.), Kluwer Academic Publishers, 1996.
Found on CV
182
Mind Matters: A Tribute to Allen Newell, D. Steier and T. Mitchell (eds.), Erlbaum, 1996.
Found on CV
181
Challenge problems for artificial intelligence. R Brooks, B Selman, T Dean, E Horvitz, TM Mitchell, NJ Nilsson Thirteenth National Conference on Artificial Intelligence-AAAI, 4, 1996.
Found on Publication Page
180
Special issue on robot learning-Introduction. JA Franklin, TM Mitchell, S Thrun Machine Learning 23 (2-3), 117-119, 1996.
Found on Publication Page
In 1995
179
Action, perception, and the realization of design. CT Mitchell Design Studies 16 (1), 4-28, 1995.
Found on Publication Page
178
"Learning Analytically and Inductively", T. Mitchell and S. Thrun, in Mind Matters: A Tribute to Allen Newell, Steier and Mitchell (eds.), Erlbaum, 1995.
Found on CV
177
"The Prospective Student's Introduction to the Robot Learning Problem," U. Nehmzow, and T.M. Mitchell, Technical Report UMCS-95-12-6, Computer Science Dept., Univ. of Manchester, December 1995.
Found on CV
176
"Lifelong Robot Learning," S. Thrun and T.M. Mitchell, in Robotics and Autonomous Systems, 15, pp. 24-46, 1995.
Found on CV
175
Lifelong robot learning. S Thrun, TM Mitchell The biology and technology of intelligent autonomous agents, 165-196, 1995.
Found on Publication Page
174
Webwatcher: A learning apprentice for the world wide web. R Armstrong, D Freitag, T Joachims, T Mitchell AAAI Spring symposium on Information gathering from Heterogeneous ..., 1995.
Found on Publication Page
173
"Learning One More Thing", S. Thrun and T.M. Mitchell, Proceedings of IJCAI 1995, Montreal, August, 1995. A longer version is available as Carnegie Mellon School of Computer Science Technical Report CMU-CS-94-184, September, 1994.
Found on CV
172
Webwatcher: Machine learning and hypertext. T Joachims, T Mitchell, D Freitag, R Armstrong Fachgruppentre en Maschinelles Lernen, Dortmund 104, 1995.
Found on Publication Page
171
"WebWatcher: Machine Learning and Hypertext," T. Joachims, R. Armstrong, D. Freitag, and T. Mitchell, German Workshop on Machine Learning, May 1995.
Found on CV
170
The prospective student's introduction to the robot learning problem. U Nehmzow, T Mitchell University of Manchester, Department of Computer Science, 1995.
Found on Publication Page
169
"WebWatcher: A Learning Apprentice for the World Wide Web", R. Armstrong, D. Freitag, T. Joachims, and T. Mitchell, in 1995 AAAI Spring Symposium on Information Gathering from Heterogeneous, Distributed Environments, March 1995.
Found on CV
168
"Using the Future to Sort Out the Present: Rankprop and Multitask Learning for Medical Risk Analysis," R. Caruana, S. Baluja, and T. Mitchell, Neural Information Processing 7, December 1995.
Found on CV
In 1994
167
"Explanation-Based Learning for Mobile Robot Perception", T.M. Mitchell, J. O'Sullivan, and S. Thrun, Proceedings of the Workshop on Learning Robots, S. Mahadevan (ed.), July, 1994.
Found on CV
165
Learning one more thing. S Thrun, TM Mitchell CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF COMPUTER SCIENCE, 1994.
Found on Publication Page
164
Experience with a learning personal assistant. TM Mitchell, R Caruana, D Freitag, J McDermott, D Zabowski Communications of the ACM 37 (7), 80-91, 1994.
Found on Publication Page
163
"Experience With a Learning Personal Assistant", T.M. Mitchell, R. Caruana, D. Freitag, J. McDermott, and D. Zabowski, Communications of the ACM, Vol. 37, No. 7, pp. 81-91, July 1994.
Found on CV
162
Explanation-based learning for mobile robot perception. TM Mitchell, J OSullivan, S Thrun Workshop on Robot Learning, Eleventh Conference on Machine Learning, 1994.
Found on Publication Page
In 1993
161
Explanation-based neural network learning for robot control. TM Mitchell, SB Thrun Advances in neural information processing systems, 287-287, 1993.
Found on Publication Page
160
An apprentice-based approach to knowledge acquisition. S Mahadevan, TM Mitchell, J Mostow, L Steinberg, PV Tadepalli Artificial Intelligence 64 (1), 1-52, 1993.
Found on Publication Page
159
"Explanation-Based Learning: A Comparison of Symbolic and Neural Network Approaches", T.M. Mitchell and S.B. Thrun, Tenth International Conference on Machine Learning, Amherst, MA, June 27-29, 1993.
Found on CV
158
Learning slopes by neural networks. R Masuoka, S Thrun, TM Mitchell Technical Report to appear, CMU Computer Science, 1993.
Found on Publication Page
157
CAP II: Making the Calendar Apprentice an Agent. S Bocionek, T Mitchell Technical Report CMU-CS-93-to-appear, Carnegie Mellon University, School of ..., 1993.
Found on Publication Page
156
A report on the NSF-EDRC study of product design processes in selected Japanese companies. E Subrahmanian, S Finger, TM Mitchell .
Found on Publication Page
155
Reinforcement learning with hidden states. LJ i Lin From animals to animats 2: Proceedings of the second international ..., 1993.
Found on Publication Page
154
23rd Annual Conference of the German Association of Computer Science (Gesellschaft fur Informatik, GI), Dresden, Germany, September, 1993.
Found on CV
153
"Integrating Inductive Neural Network Learning and Explanation-Based Learning", Thrun, S., and Mitchell, T.M., Proceedings of the 1993 International Joint Conference on Artificial Intelligence, August 1993.
Found on CV
152
Integrating inductive neural network learning and explanation-based learning. SB Thrun, TM Mitchell IJCAI, 930-936, 1993.
Found on Publication Page
151
"Explanation-Based Neural Network Learning for Robot Control", T.M. Mitchell and S.B. Thrun, Advances in Neural Information Processing Systems 5, Hanson, Cowan, and Giles (eds.), Morgan- Kaufmann Press, 1993, pp. 287-294.
Found on CV
150
The engineering design research center of carnegie mellon university. GH Demes, SJ Fenves, IE Grossmann, CT Hendrickson, TM Mitchell, ... Proceedings of the IEEE 81 (1), 10-24, 1993.
Found on Publication Page
149
Apprentissage symbolique: une approche de l'intelligence artificielle. Y Kodratoff, RS Michalski, JG Carbonell, TM Mitchell Cpadus-ditions, 1993.
Found on Publication Page
148
"An Apprentice-Based Approach to Knowledge Acquisition", Mahadevan, S., Mitchell, T., Mostow, D.J., Steinberg, L., Tadepalli, P., Artificial Intelligence Vol 64, No. 1, (November 1993), pages 1-52.
Found on CV
147
A comparative analysis of chunking and decision-analytic control. O Etzioni, TM Mitchell The Soar papers (vol. II), 713-718, 1993.
Found on Publication Page
146
"The Engineering Design Research Center of Carnegie Mellon University", G.H. Demes, S.J. Fenves, I.E. Grossmann, C.T. Hendrickson, T.M. Mitchell, F.B. Prinz, D.P. Siewiorek, E. Subramanian, S. Talukdar, A. Westerberg, Proceedings of the IEEE, Special Issue on Engineering Research Centers, Invited paper, Vol. 81, No. 1, pp. 10-24, January, 1993.
Found on CV
145
Office automation systems that are programmed by their users. S Bocionek, TM Mitchell InformatikWirtschaftGesellschaft, 214-219, 1993.
Found on Publication Page
144
"Machine Learning and Human Interface for the CMU Navlab" Chuck Thorpe, Haralabos Athanassiou, Jennifer Kay, Tom Mitchell, and Dean Pomerleau, in Proc. 6th Int. Symposium on Robotics Research, T. Kanade and R. Paul, eds., 1993.
Found on CV
In 1992
143
"A Personal Learning Apprentice", Dent, L., Boticario, J., McDermott, J., Mitchell, T., and Zabowski, D., 1992 National Conference on AI, July, 1992.
Found on CV
142
Memory approaches to reinforcement learning in non-Markovian domains. LJ Lin, TM Mitchell Carnegie-Mellon University. Department of Computer Science, 1992.
Found on Publication Page
140
A personal learning apprentice. L Dent, J Boticario, JP McDermott, TM Mitchell, D Zabowski AAAI, 96-103, 1992.
Found on Publication Page
139
"Interfaces that Learn: A Learning Apprentice for Calendar Management", Jourdan, J., Dent, L., McDermott, J., Mitchell, T., and D. Zabowski, in Machine Learning Methods for Planning and Scheduling, S. Minton (ed.), Morgan-Kaufmann Press, 1992. A preliminary version of this paper appears as Carnegie Mellon School of Computer Science Technical Report CMU-CS-91-135, May 1991.
Found on CV
138
"Memory Approaches to Reinforcement Learning in Non-Markovian Domains", L.J. Lin and T.M. Mitchell, Carnegie Mellon School of Computer Science Technical Report CMU-CS-92-138, May 1992.
Found on CV
137
Using EBG to Simulate Human Learning from Examples and Learning by Doing, Qin, Y., Mitchell, T., and H. Simon, Proceedings of the Florida AI Research Symposium, April 1992, pp. 235-239.
Found on CV
In 1991
136
"Justification-Based Refinement of Expert Knowledge", J.C. Schlimmer, T.M. Mitchell, and J. McDermott, in G. Piatetsky-Shapiro and W. Frawley (Eds.), Knowledge Discovery in Databases, AAAI Press, pp. 397-410, 1991. (an earlier version appears in Proceedings of the Workshop on Knowledge Discovery in Databases, workshop held in conjunction with IJCAI-89, Detroit, MI, August 1989.)
Found on CV
135
"Learning Reliable Manipulation Strategies without Initial Physical Models", A. Christiansen, M. Mason, and T.M. Mitchell, Robotics and Autonomous Systems, vol. 8, pp. 7-18, 1991. (Reprinted from Proceedings of the IEEE International Conference on Robotics and Automation, May, 1990).
Found on CV
133
Also Rutgers University Computer Science Technical Report, August, 1991.
Found on CV
132
Ambler: a six-legged planetary rover. E Krotkov, J Bares, T Kanade, T Mitchell, R Simmons, R Whittaker Fifth International Conference on Advanced Robotics, 717-722, 1991.
Found on Publication Page
131
A Learning Apprentice for Calendar Management. J Jourdan, L Dent, J Mcdermott, T Mitchell, D Zabowski .
Found on Publication Page
130
Ambler: A Legged Planetary Rover. E Krotkov, J Bares, M Hebert, T Kanade, T Mitchell, R Simmons, ... 1990 Annual Research Review, The Robotics Institute, Carnegie Mellon ..., 1991.
Found on Publication Page
129
Theo: A framework for self-improving systems. TM Mitchell, J Allen, P Chalasani, J Cheng, O Etzioni, M Ringuette, ... Architectures for intelligence, 323-356, 1991.
Found on Publication Page
128
The MONKs comparison of learning algorithms. Introduction and survey. S Thrun, T Mitchell, J Cheng The MONKs problems-a performance comparison of different learning ..., 1991.
Found on Publication Page
127
The monk's problems a performance comparison of different learning algorithms. SB Thrun, J Bala, E Bloedorn, I Bratko, B Cestnik, J Cheng, K De Jong, ... .
Found on Publication Page
126
"Theo: A Framework for Self-Improving Systems", Tom M. Mitchell, John Allen, Prasad Chalasani, John Cheng, Oren Etzioni, Marc N. Ringuette, Jeffrey C. Schlimmer, in "Architectures for Intelligence", K. Vanlehn (ed.), Lawrence Erlbaum Associates, New Jersey, 1991, pp. 323-356.
Found on CV
125
"Plan-Then-Compile Architectures", T.M. Mitchell, Proceedings of the AAAI Spring Symposium on Integrated Intelligent Architectures, Stanford Universtiy, March 1991.
Found on CV
124
The MONKs Problems. S Thrun, J Bala, E Bloedorn, I Bratko, B Cestnik, K De Jong, S Dzeroski, ... A Performance Comparison of Different Learning Algorithms. Carnegi Mellon ..., 1991.
Found on Publication Page
123
Learning reliable manipulation strategies without initial physical models. AD Christiansen, MT Mason, TM Mitchell Robotics and Autonomous Systems 8 (1-2), 7-18, 1991.
Found on Publication Page
121
"The MONK's Problems: A Performance Comparison of Different Learning Algorithms", S. Thrun, et al., Carnegie Mellon School of Computer Science Technical Report CMU-CS-91-197, December 1991.
Found on CV
In 1990
120
Learning Robots. TM Mitchell 90 Proceedings of the 4th Australian Joint Conference on AI, 1990.
Found on Publication Page
119
Embedding learning in a general frame-based architecture. T Tanaka, TM Mitchell International Journal of Pattern Recognition and Artificial Intelligence 4 ..., 1990.
Found on Publication Page
118
Can we build learning robots?. TM Mitchell Proceedings of the eighth biennial conference of the Canadian Society for ..., 1990.
Found on Publication Page
117
"LEAP: A Learning Apprentice for VLSI Design", T. Mitchell, S. Mahadevan, and L. Steinberg, Ninth International Joint Conference on Artificial Intelligence, August 1985. Also a chapter in Machine Learning: An Artificial Intelligence Approach, Vol. III, Kodratoff and Michalski (eds.), Morgan Kaufmann Press, 1990.
Found on Publication Text
115
"Machine Learning", T. Mitchell, B. Buchanan, G. DeJong, T. Dietterich, P. Rosenbloom, A. Waibel, Annual Review of Computer Science, vol. 4, 1990, pp. 417-433.
Found on CV
114
"Becoming Increasingly Reactive", T.M. Mitchell, 1990 National Conference on AI, Cambridge, MA, August, 1990.
Found on CV
113
"Embedding Learning in a General Frame-Based Architecture", T. Tanaka and T.M. Mitchell, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 4, No. 2, pp. 125-145, June 1990. An earlier version of this paper appeared in Proceedings of the IEEE International Workshop on Tools for Artificial Intelligence '89, IEEE Computer Society Press, George Mason University, October 1989, pp. 77-84.
Found on CV
112
"LEAP: A Learning Apprentice for VLSI Design", T. Mitchell, S. Mahadevan, and L. Steinberg, Ninth International Joint Conference on Artificial Intelligence, August 1985. Also a chapter in Machine Learning: An Artificial Intelligence Approach, Vol. III, Kodratoff and Michalski (eds.), Morgan Kaufmann Press, 1990.
Found on CV
111
. "The Need for Biases in Learning Generalizations", T.M. Mitchell, Rutgers Computer Science Department Technical Report CBM-TR-117, May, 1980. Reprinted in Readings in Machine Learning, J. Shavlik and T. Dietterich, eds., Morgan Kaufmann, 1990.
Found on CV
110
"Learning Robots", T.M. Mitchell, Proceedings of the 1990 Australian National Conference on Artificial Intelligence, November, 1990.
Found on CV
In 1989
108
(written January 1988). (also CMU Computer Science Technical Report CMU-CS-89-106 January, 1989).
Found on CV
107
"An Autonomous Rover for Exploring Mars", J. Bares, M. Hebert, T. Kanade, E. Krotkov, T. Mitchell, R. Simmons, W. Whittaker, IEEE Computer, Special Issue on Autonomous Intelligent Machines, June, 1989 pp18-26.
Found on CV
106
Autonomous Planetary Rover at Carnegie Mellon. T Kanade, T Mitchell, W Whittaker Technical Report CMU-RI-TR-89-3. Camenie Mellon, 1989.
Found on Publication Page
105
Design of a Planetary Rover. E Krotkov, J Bares, M Hebert, T Kanade, T Mitchell, R Simmons, ... 1988 Annual Research Review, 9-24, 1989.
Found on Publication Page
104
Ambler: An autonomous rover for planetary exploration. J Bares, M Hebert, T Kanade, E Krotkov, T Mitchell, R Simmons, ... Computer 22 (6), 18-26, 1989.
Found on Publication Page
103
"On Becoming Reactive", J. Blythe and T.M. Mitchell, Proceedings of the 6th International Workshop on Machine Learning, Cornell University, June, 1989.
Found on CV
102
"A Task Control Architecture for Mobile Robots", R. Simmons and T. Mitchell, in Proceedings of the 1989 AAAI Spring Symposium on Robot Navigation, Palo Alto, March, 1989.
Found on CV
101
"Experiments in Robot Learning", M.T. Mason, A.D. Christiansen, and T.M. Mitchell, Proceedings of the 6th International Workshop on Machine Learning, Cornell University, June, 1989, pp. 141-145.
Found on CV
99
"A Case Study in Robot Exploration", L. Lin, A. Philips, T.M. Mitchell, R. Simmons, Robotics Institute Technical Report CMU-RI-89-001, CMU, January 1989.
Found on CV
98
"A Comparative Analysis of Chunking and Decision-Analytic Control", O. Etzioni and T. Mitchell, in Proceedings of the 1989 AAAI Spring Symposium on Limited Rationality and Artificial Intelligence, Palo Alto, March, 1989.
Found on CV
In 1988
97
"Toward a Learning Robot", T.M. Mitchell, M.T. Mason, and A.D. Christiansen, "Proceedings of the Workshop on Representation and Learning in an Autonomous Agent", Portugal, November 1988.
Found on CV
In 1987
96
"Artificial Intelligence Systems in the Space Station", T. M. Mitchell, Proceedings of the Symposium on Human Factor Needs in Space Station Design, National Academy of Sciences, Washington D.C., January 29-30, 1987.
Found on CV
94
"Machine Learning and Planning in Reactive Environments", J. G. Carbonell, M. T. Mason, and T. M. Mitchell, "Proceedings of The Second Annual NASA Artificial Intelligence Research Forum", NASA Ames Research Center, CA, pp. 254-262. November, 1987.
Found on CV
In 1986
93
Progress toward a knowledge-based aid for mechanical design. NA Langrana, TM Mitchell, N Ramachandran Rutgers University, Department of Computer Science, Laboratory for Computer ..., 1986.
Found on Publication Page
92
"Explanation-Based Generalization: A Unifying View", T. Mitchell, R. Keller, and S. Kedar-Cabelli, Machine Learning, vol. 1, issue 1, January, 1986.
Found on CV
91
Learning apprentice systems research at Schlumberger. H Winston, R Smith, M Kleyn, T Mitchell, B Buchanan Machine Learning, 379-383, 1986.
Found on Publication Page
90
Learning improved integrity constraints and schemas from exceptions in data and knowledge bases. A Borgida, T Mitchell, KE Williamson On Knowledge Base Management Systems, 259-286, 1986.
Found on Publication Page
89
Explanation-based generalization: A unifying view. TM Mitchell, RM Keller, ST Kedar-Cabelli Machine learning 1 (1), 47-80, 1986.
Found on Publication Page
88
"Learning Improved Integrity Constraints and Schemas from Exceptions in Data and Knowledge Bases", A. Borgida, T.M. Mitchell, and K.E. Williamson. On Knowledge Base Management Systems: Integrating Artificial Intelligence and Database Technologies, J. Mylopoulos and M. Brodie (eds.), Springer-Verlag, 1986.
Found on CV
87
"Progress Toward a Knowledge-Based Aid for Mechanical Design", N.A. Langrana and T.M. Mitchell, ASME Symposium on Integrated Intelligent Manufacturing: Analysis and Synthesis, December 1986.
Found on CV
86
A learning apprentice system for VLSI design. TM Mitchell, S Mahadevan, LI Steinberg Machine Learning, 203-206, 1986.
Found on Publication Page
85
Machine Learning: An Artificial Intelligence Approach. Volume 2 Michalski, Carbonell, and Mitchell, eds., Morgan-Kaufman, 1986.
Found on CV
84
Machine Learning: A Guide to Current Research, Mitchell, Carbonell, and Michalski, eds., Kluwer Academic Publishers, 1986.
Found on CV
83
"Learning in Knowledge Base Management Systems", T. M. Mitchell, On Knowledge Base Management Sytems: Integrating Artificial Intelligence and Database Technologies, J. Mylopoulos and M. Brodie (eds.), Springer-Verlag, 1986.
Found on CV
In 1985
82
A knowledge-based approach to design. TM Mitchell, LI Steinberg, JS Shulman IEEE Transactions on Pattern Analysis and Machine Intelligence 7 (5), 502-510, 1985.
Found on Publication Page
81
(received Best Paper Award). A slightly modified version of this paper appeared subsequently in IEEE Design and Test, February, 1985.
Found on CV
80
The redesign system: a knowledge-based approach to VLSI CAD. LI Steinberg, TM Mitchell IEEE Design & Test of Computers 2 (1), 45-54, 1985.
Found on Publication Page
79
Representation and Use of Explicit Justifications for Knowledge Base Refinements. RG Smith, HA Winston, TM Mitchell, BG Buchanan IJCAI, 673-680, 1985.
Found on Publication Page
78
LEAP: A learning apprentice for VLSI. TM Mitchell, S Mahadevan, LI Steinberg Proceedings of the 9th international joint conference on Artificial ..., 1985.
Found on Publication Page
77
"Representation and Use of Explicit Justifications for Knowledge Base Refinement", R.G. Smith, H.A. Winston, T. Mitchell, and B. Buchanan, Ninth International Joint Conference on Artificial Intelligence, August 1985.
Found on CV
76
"A Knowledge-Based Approach to Design", T. Mitchell, L. Steinberg, and J. Shulman, IEEE Transactions on Pattern Analysis and Machine Intelligence, September, 1985. An earlier version of this paper appeared in Proceedings of the IEEE Workshop on Principles of Knowledge-Based Systems, Denver, Colorado, December 1984.
Found on CV
In 1984
75
Toward combining empirical and analytical methods for inferring heuristics. TM Mitchell Proc. of the international NATO symposium on Artificial and human ..., 1984.
Found on Publication Page
74
A knowledge based approach to VLSI CAD the redesign system. LI Steinberg, TM Mitchell Proceedings of the 21st Design Automation Conference, 412-418, 1984.
Found on Publication Page
73
. "A Knowledge-Based Approach to VLSI CAD", L. Steinberg and T. Mitchell, in Proceedings of the 21st Design Automation Conference, IEEE and ACM, Albequerque, New Mexico, June 1984
Found on CV
72
VEXED: A Knowledge-Based VLSI Design Consultant. TM Mitchell, LI Steinberg, JS Shulman Department of Computer Science, Rutgers University, 1984.
Found on Publication Page
71
. "Toward Combining Empirical and Analytical Methods for Inferring Heuristics," Tom M. Mitchell, in Artificial and Human Intelligence, Elithorn and Banerji (eds.), North-Holland, 1984. Also Rutgers Computer Science Department Technical Report LCSR-TR-27, 1981.
Found on CV
In 1983
70
Machine learning: An artificial intelligence approach. TM Mitchell, JR Anderson, JG Carbonel, RS Michalski Vol II, 1983.
Found on Publication Page
69
. "Goal-Directed Learning", T. Mitchell and R. Keller, in Proceedings of the Second International Workshop on Machine Learning, Allerton, Illinois, June 1983.
Found on CV
68
Machine learning I: An AI Approach. RS Michalski, J Carbonell, TM Mitchell Morgan Kaufmann, Los Altos, CA, 1983.
Found on Publication Page
67
. "Constructing an Expert System," B. G. Buchanan, R. Bechtal, J. Bennett, W. Clancey, C. Kulikowski, T. Mitchell, and D. Waterman, in Building Expert Systems, F. Hayes-Roth, D. Lenat, and D. Waterman (eds.), Prentice-Hall, 1983.
Found on CV
66
. "An Intelligent Aid for Circuit Redesign", T. Mitchell, L. Steinberg, Smadar Kedar-Cabelli, Van E. Kelly, Jeffrey Shulman, and Timothy Weinrich, in Proceedings of the Third National Conference on Artificial Intelligence, Washington D.C., August 1983.
Found on CV
65
Machine Learning, Part I: A Historical and Methodological Analysis. JG Carbonell, RS Michalski, TM Mitchell .
Found on Publication Page
64
A historical and methodological analysis. RS Michalski, JG Carbonell, TM Mitchell Al Magazine, 69-79, 1983.
Found on Publication Page
63
Machine learning: A historical and methodological analysis. JG Carbonell, RS Michalski, TM Mitchell AI Magazine 4 (3), 69, 1983.
Found on Publication Page
62
A knowledge based approach to VLSI CAD. LI Steinberg, TM Mitchell RUTGERS-THE STATE UNIV NEW BRUNSWICK NJ DEPT OF COMPUTER SCIENCE, 1983.
Found on Publication Page
61
An Intelligent Aid for Circuit Redesign. TM Mitchell, LI Steinberg, ST Kedar-Cabelli, VE Kelly, JS Shulman, ... AAAI, 274-278, 1983.
Found on Publication Page
59
An overview of machine learning. JG Carbonell, RS Michalski, TM Mitchell Machine learning, 3-23, 1983.
Found on Publication Page
58
Learning by experimentation: Acquiring and refining problem-solving heuristics. TM Mitchell, PE Utgoff, R Banerji Machine Learning, 163-190, 1983.
Found on Publication Page
57
Constructing an expert system. BG Buchanan, D Barstow, R Bechtal, J Bennett, W Clancey, C Kulikowski, ... Building expert systems 50, 127-167, 1983.
Found on Publication Page
56
Machine Learning: An Artificial Intelligence Approach, Michalski, Carbonell, and Mitchell, eds., Tioga Press, 1983.
Found on CV
54
. "Learning and Problem-Solving", T. Mitchell, in Proceedings of the Eighth International Joint Conference on Artificial Intelligence, Karlsruhe, Germany, August 1983 (Computers and Thought Award Paper).
Found on CV
53
. "Learning by Experimentation: Acquiring and Modifying Problem-Solving Heuristics", T. Mitchell, P. Utgoff, and R. Banerji, in Machine Learning, Michalski, Carbonell, and Mitchell (eds.), Tioga Press, 1983, pp.163-190. Also Rutgers Computer Science Department Technical Report LCSR- TR-31.
Found on CV
52
. "An Overview of Machine Learning", J. Carbonell, R. Michalski, and T. Mitchell, in Machine Learning, Michalski, Carbonell, and Mitchell (eds.), Tioga Press, 1983.
Found on CV
51
Goal directed learning. TM Mitchell, R Keller Proceedings of the International Machine Learning Workshop, 117-118, 1983.
Found on Publication Page
In 1982
50
. "Generalization as Search", T.M. Mitchell, Artificial Intelligence, Volume 18, No. 2, 1982. Also appears in Readings in Artificial Intelligence, Webber and Nilsson (eds.), Tioga Press, 1981, pp. 517-542.
Found on CV
49
. "Data Base Management Systems and Expert Systems for Computer Aided Design", G. Lafue and T. Mitchell, in Proceedings of the IFIP Working Conference on CAD System Frameworks, Roros, Norway, June, 1982.
Found on CV
48
Learning by experimentation: acquiring and modifying problem-solving heuristics. TM Mitchell, PE Utgoff, RB Banerji Laboratory for Computer Science Research, Rutgers University, 1982.
Found on Publication Page
46
. "Learning from Solution Paths: An Approach to the Credit Assignment Problem", D. Sleeman, P. Langley, and T. Mitchell, AI Magazine, vol. 3, no. 2, 1982. Also Carnegie Mellon University Department of Psychology CIP Working Paper No. 443.
Found on CV
45
Learning from solution paths: An approach to the credit assignment problem. D Sleeman, P Langley, TM Mitchell AI Magazine 3 (2), 48, 1982.
Found on Publication Page
44
Data base management systems and expert systems for CAD. Rutgers University. Laboratory for Computer Science Research, ... Laboratory for Computer Science Research, Rutgers University, 1982.
Found on Publication Page
43
Acquisition of appropriate bias for inductive concept learning. PE Utgoff, TM Mitchell Laboratory for Computer Science Research, Rutgers University, 1982.
Found on Publication Page
42
. "Acquisition of Appropriate Bias for Inductive Concept Learning", P. Utgoff and T. Mitchell, Proceedings of the Second National Conference on Artificial Intelligence, Pittsburgh, August, 1982, pp. 414-417.
Found on CV
In 1981
41
Learning Problem-Solving Heuristics Through Practice. TM Mitchell, PE Utgoff, B Nudel, RB Banerji IJCAI 7, 127-134, 1981.
Found on Publication Page
40
. "Learning Problem-Solving Heuristics by Practice", T.M. Mitchell, P. Utgoff, B. Nudel, R. Banerji, Proceedings of the 7th International Joint Conference on Artificial Intelligence, Aug., 1981, pp. 127-134.
Found on CV
39
. "Representations for Reasoning about Digital Circuits", T.M. Mitchell, L. Steinberg, R.G.Smith, P. Schooley, V. Kelly. Proceedings of the 7th International Joint Conference on Artificial Intelligence, Aug., 1981, pp. 343-344. Also Rutgers Computer Science Department Technical Report LCSR- TR-11.
Found on CV
38
Representations for reasoning about digital circuits. TM Mitchell, L Steinberg, RG Smith, H Jacobs, P Schooley RUTGERS-THE STATE UNIV NEW BRUNSWICK NJ DEPT OF COMPUTER SCIENCE, 1981.
Found on Publication Page
In 1980
37
Learning problem-solving heuristics by experimentation. TM Mitchell, PE Utgoff, RB Banerji Department of Computer Science, Rutgers University, 1980.
Found on Publication Page
36
Description languages and learning algorithms: A paradigm for comparison. RB Banerji, TM Mitchell Department of Computer Science, Rutgers University, 1980.
Found on Publication Page
35
The need for biases in learning generalizations. TM Mitchell Department of Computer Science, Laboratory for Computer Science Research ..., 1980.
Found on Publication Page
34
. "Description Languages and Learning Algorithms: A Paradigm for Comparison", R.B. Banerji and T.M. Mitchell, International Journal of Policy Analysis and Information Systems, special issue on Knowledge Acquisition and Induction, vol. 4, p. 197, 1980. Also Rutgers Computer Science Department Technical Report CBM-TR-107.
Found on CV
In 1979
33
An analysis of generalization as a search problem. TM Mitchell Proceedings of the 6th international joint conference on Artificial ..., 1979.
Found on Publication Page
32
Models of Learning Systems. BG Buchanan, TM Mitchell, RG Smith, CR Johnson Jr STANFORD UNIV CALIF DEPT OF COMPUTER SCIENCE, 1979.
Found on Publication Page
In 1978
31
. "Applications of Artificial Intelligence for Chemical Inference XXV. A Computer Program for Automated Empirical 13C-NMR Rule Formation", T.M. Mitchell and G.M. Schwenzer, Organic Magnetic Resonance, vol. 11, no. 8, 1978, pp. 378-384.
Found on CV
30
"Models of Learning Systems," B.G. Buchanan, T.M. Mitchell, R.G. Smith, C.R. Johnson, in Encyclopedia of Computer Science and Technology, vol. 11, Marcel Dekker, New York, NY, pp. 24-51. 1978.
Found on Publication Text
29
Version spaces: an approach to concept learning. TM Mitchell STANFORD UNIV CALIF DEPT OF COMPUTER SCIENCE, 1978.
Found on Publication Page
28
Considerations for Microprocessor-Based Terminal Design. RG Smith, TM Mitchell STANFORD UNIV CALIF DEPT OF COMPUTER SCIENCE, 1978.
Found on Publication Page
27
. "Models of Learning Systems", B.G. Buchanan, T.M. Mitchell, R.G. Smith, and C.R. Johnson, in Encyclopedia of Computer Science and Technology, Marcel Dekker, Inc., New York, vol. 11, 1978, pp.24-50.
Found on CV
26
Application of artificial intelligence for chemical inference. XXV. A computer program for automated empirical 13C NMR rule formation. TM Mitchell, GM Schwenzer Organic Magnetic Resonance 11 (8), 378-384, 1978.
Found on Publication Page
25
. "Version Spaces: An Approach to Concept Learning", T.M. Mitchell, Ph.D. dissertation, Electrical Engineering Department, Stanford University, December, 1978. Also Stanford Computer Science Department Technical Report STAN-CS-78-711. 204 pages.
Found on CV
24
. "Model-Directed Learning of Production Rules", B.G. Buchanan and T.M. Mitchell, in Pattern Directed Inference Systems, D.A. Waterman and F. Hayes-Roth eds., Academic Press, New York, 1978, pp. 297-312. Also Stanford Heuristic Programming Project Memo HPP-77-6, and Stanford Computer Science Department Report No. STAN-CS-77-597.
Found on CV
23
A computer program for automated empirical C-13 nmr rule formation. TM Mitchell, GM Schwenzer Org. Magn. Reson. 11, 378-384, 1978.
Found on Publication Page
22
. "Considerations for Microprocessor-Based Terminal Designs" R.G. Smith and T.M. Mitchell, Invited paper, Proceedings of the Twelfth Annual Asilomar Conference on Circuits, Systems, and Computers, Pacific Grove, CA, November, 1978. Also Stanford Computer Science Department Technical Report HP-78-22.
Found on CV
In 1977
21
A model for learning systems. RG Smith, TM Mitchell, RA Chestek, BG Buchanan STANFORD UNIV CA DEPT OF COMPUTER SCIENCE, 1977.
Found on Publication Page
20
Model-directed learning of production rules. BG Buchanan, TM Mitchell STANFORD UNIV CA DEPT OF COMPUTER SCIENCE, 1977.
Found on Publication Page
19
Version spaces: A candidate elimination approach to rule learning. TM Mitchell Proceedings of the 5th international joint conference on Artificial ..., 1977.
Found on Publication Page
18
. "Version Spaces: A Candidate Elimination Approach to Rule Learning", T.M. Mitchell, Proceedings of the 5th International Joint Conference on Artificial Intelligence, Cambridge MA, August 1977, pp. 305-310.
Found on CV
17
Version spaces: An approach to rule revision during rule induction. TM Mitchell Department of Computer Science, Stanford University, 1977.
Found on Publication Page
16
Computer-Assisted Structure Elucidation Using Automatically Acquired 13C NMR Rules. GM Schwenzer, TM Mitchell Computer-Assisted Structure Elucidation, ACS Symposium Series, 58-76, 1977.
Found on Publication Page
15
. "Computer Assisted Structure Elucidation Using Automatically Acquired 13C-NMR Rules", G.M. Schwenzer and T.M. Mitchell, in Computer Assisted Structure Elucidation, American Chemical Society Symposium Series, Volume 54, D. H. Smith editor, Washington D.C., 1977, pp. 58-76.
Found on CV
In 1955
Unspecified
13
"Office Automation Systems that are Programmed by their Users", S. Bocionek and T.M. Mitchell.
Found on CV
12
O ce Automation Systems that are\ Programmed" by their Users. S Bocionek, TM Mitchell Proceedings der 23, 0.
Found on Publication Page
11
Automated fMRI Feature Abstraction using Neural Network Clustering Techniques. RS Niculescu, TM Mitchell .
Found on Publication Page
9
Semi-supervised Data Clustering with Coupled Non-negative Matrix Factorization: Sub-category Discovery of Noun Phrases in NELLs Knowledge Base. C Liu, T Mitchell ml. cmu. edu, 1-19, 0.
Found on Publication Page
8
Predicting Human Brain Activity Associated with Noun Meanings. TM Mitchell, SV Shinkareva, A Carlson, KM Chang, VL Malave, RA Mason, ... Citeseer. REFERENCES REFERENCES, 0.
Found on Publication Page
7
Using the future to sort out the present: Rankprop and multitask learning for medical risk analysis. R Caruana, S Baluja, T Mitchell NIPS95, 959-965, 0.
Found on Publication Page
6
A Spousal Relation Begins with a Deletion of engage and Ends with an Addition of divorce: Learning State Changing Verbs from Wikipedia Revision History. DT Wijaya, N Nakashole, TM Mitchell .
Found on Publication Page
5
Mapping Verbs In Different Languages to Knowledge Base Relations using Web Text as Interlingua. DT Wijaya, TM Mitchell .
Found on Publication Page
4
1983. R Michalski, J Carbonell, T Mitchell Machine Learning: An Artificial Intelligence Approach, 0.
Found on Publication Page
2
Exploring Hierarchical User Feedback in Email Clustering, Yifen Huang and Tom Mitchell.
Found on CV
1
"A Neurosemantic Theory of Concrete Noun Representation Based on the Underlying Brain Codes," Marcel A. Just, Vladimir L. Cherkassky, Sandesh Aryal, Tom M. Mitchell, PLoS ONE 5(1): e8622
Found on CV
