Tom M. Mitchell

Evangelos E. Papalexakis, Tom M. Mitchell, Nicholas D. Sidiropoulos, Christos Faloutsos, Partha Pratim Talukdar, Brian Murphy: Scoup-SMT: Scalable Coupled Sparse Matrix-Tensor Factorization. CoRR abs/1302.7043 (2013)

Alona Fyshe, Emily B. Fox, David B. Dunson, Tom M. Mitchell: Hierarchical Latent Dictionaries for Models of Brain Activation. Journal of Machine Learning Research - Proceedings Track 22: 409-421 (2012)

Gustavo Sudre, Dean Pomerleau, Mark Palatucci, Leila Wehbe, Alona Fyshe, Riitta Salmelin, Tom M. Mitchell: Tracking neural coding of perceptual and semantic features of concrete nouns. NeuroImage 62(1): 451-463 (2012)

Tom M. Mitchell: Never Ending Learning. ECAI 2012: 5

Svetlana V. Shinkareva, Vicente L. Malave, Robert A. Mason, Tom M. Mitchell, Marcel Adam Just: Commonality of neural representations of words and pictures. NeuroImage 54(3): 2418-2425 (2011)

Kai-min Kevin Chang, Tom M. Mitchell, Marcel Adam Just: Quantitative modeling of the neural representation of objects: How semantic feature norms can account for fMRI activation. NeuroImage 56(2): 716-727 (2011)

Ni Lao, Tom M. Mitchell, William W. Cohen: Random Walk Inference and Learning in A Large Scale Knowledge Base. EMNLP 2011: 529-539

Thahir Mohamed, Estevam R. Hruschka Jr., Tom M. Mitchell: Discovering Relations between Noun Categories. EMNLP 2011: 1447-1455

Tom M. Mitchell: Neural Representations of Word Meanings. INTERSPEECH 2011

Andrew Carlson, Justin Betteridge, Bryan Kisiel, Burr Settles, Estevam R. Hruschka Jr., Tom M. Mitchell: Toward an Architecture for Never-Ending Language Learning. AAAI 2010

Edith Law, Burr Settles, Tom M. Mitchell: Learning to Tag from Open Vocabulary Labels. ECML/PKDD (2) 2010: 211-226

Andrew Carlson, Justin Betteridge, Richard C. Wang, Estevam R. Hruschka Jr., Tom M. Mitchell: Coupled semi-supervised learning for information extraction. WSDM 2010: 101-110

Rebecca A. Hutchinson, Radu Stefan Niculescu, Timothy A. Keller, Indrayana Rustandi, Tom M. Mitchell: Modeling fMRI data generated by overlapping cognitive processes with unknown onsets using Hidden Process Models. NeuroImage 46(1): 87-104 (2009)

Justin Betteridge, Andrew Carlson, Sue Ann Hong, Estevam R. Hruschka Jr., Edith L. M. Law, Tom M. Mitchell, Sophie H. Wang: Toward Never Ending Language Learning. AAAI Spring Symposium: Learning by Reading and Learning to Read 2009: 1-2

Yifen Huang, Tom M. Mitchell: Toward Mixed-Initiative Email Clustering. AAAI Spring Symposium: Agents that Learn from Human Teachers 2009: 71-78

Kai-min Kevin Chang, Vladimir Cherkassky, Tom M. Mitchell, Marcel Adam Just: Quantitative modeling of the neural representation of adjective-noun phrases to account for fMRI activation. ACL/IJCNLP 2009: 638-646

Mark Palatucci, Dean Pomerleau, Geoffrey E. Hinton, Tom M. Mitchell: Zero-shot Learning with Semantic Output Codes. NIPS 2009: 1410-1418

Tom M. Mitchell, Justin Betteridge, Andrew Carlson, Estevam R. Hruschka Jr., Richard C. Wang: Populating the Semantic Web by Macro-reading Internet Text. International Semantic Web Conference 2009: 998-1002

Tom M. Mitchell: Computational Models of Neural Representations in the Human Brain. ALT 2008: 5-6

Tom M. Mitchell: Computational Models of Neural Representations in the Human Brain. Discovery Science 2008: 26-27

Danny Hillis, John McCarthy, Tom M. Mitchell, Erik T. Mueller, Doug Riecken, Aaron Sloman, Patrick Henry Winston: In Honor of Marvin Minsky's Contributions on his 80th Birthday. AI Magazine 28(4): 103-110 (2007)

Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat Rao: A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints. IJCAI 2007: 155-160

Lillian Y. Chang, Nancy S. Pollard, Tom M. Mitchell, Eric P. Xing: Feature selection for grasp recognition from optical markers. IROS 2007: 2944-2950

Tom M. Mitchell: Learning, Information Extraction and the Web. ECML/PKDD 2007: 1

Mark Palatucci, Tom M. Mitchell: Classification in Very High Dimensional Problems with Handfuls of Examples. PKDD 2007: 212-223

Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat Rao: Bayesian Network Learning with Parameter Constraints. Journal of Machine Learning Research 7: 1357-1383 (2006)

Tom M. Mitchell, Sophie H. Wang, Yifen Huang, Adam Cheyer: Extracting Knowledge about Users' Activities from Raw Workstation Contents. AAAI 2006: 181-186

Rebecca A. Hutchinson, Tom M. Mitchell, Indrayana Rustandi: Hidden process models. ICML 2006: 433-440

Yifen Huang, Tom M. Mitchell: Text clustering with extended user feedback. SIGIR 2006: 413-420

Tom M. Mitchell, Hector J. Levesque: The 2005 AAAI Classic Paper Awards. AI Magazine 26(4): 98-99 (2005)

Gregory F. Cooper, Vijoy Abraham, Constantin F. Aliferis, John M. Aronis, Bruce G. Buchanan, Rich Caruana, Michael J. Fine, Janine E. Janosky, Gary Livingston, Tom M. Mitchell: Predicting dire outcomes of patients with community acquired pneumonia. Journal of Biomedical Informatics 38(5): 347-366 (2005)

Qiong Chen, Tom M. Mitchell: Learning Topic-Based Mixture Models for Factored Classification. CIMCA/IAWTIC 2005: 25-31

Qiong Chen, Tom M. Mitchell: Learning Topic-Based Mixture Models for Factored Classification. CIMCA/IAWTIC 2005: 1114-1120

Tom M. Mitchell: Machine Learning for Analyzing Human Brain Function. PAKDD 2005: 1

Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat Rao: Exploiting Parameter Related Domain Knowledge for Learning in Graphical Models. SDM 2005

Tom M. Mitchell, Rebecca A. Hutchinson, Radu Stefan Niculescu, Francisco Pereira, Xuerui Wang, Marcel Adam Just, Sharlene Newman: Learning to Decode Cognitive States from Brain Images. Machine Learning 57(1-2): 145-175 (2004)

Yifen Huang, Dinesh Govindaraju, Tom M. Mitchell, Vitor Rocha de Carvalho, William W. Cohen: Inferring Ongoing Activities of Workstation Users by Clustering Email. CEAS 2004

William W. Cohen, Vitor R. Carvalho, Tom M. Mitchell: Learning to Classify Email into ``Speech Acts''. EMNLP 2004: 309-316

Tom M. Mitchell: Intelligent Workstation Agents and Unstructured Workstation Data. IAT 2004: 6

Daniel B. Neill, Andrew W. Moore, Francisco Pereira, Tom M. Mitchell: Detecting Significant Multidimensional Spatial Clusters. NIPS 2004

Tom M. Mitchell: Intelligent Workstation Agents and Unstructured Workstation Data. Web Intelligence 2004: 6

Peter E. Hart, Nils J. Nilsson, Ray Perrault, Tom M. Mitchell, Casimir A. Kulikowski: In Memoriam: Charles Rosen, Norman Nielsen, and Saul Amarel. AI Magazine 24(1): 6-12 (2003)

David Mike Hamilton, Tom M. Mitchell, Carol McKenna Hamilton: AI Matures and Flourishes in North America. IEEE Intelligent Systems 18(4): 87- (2003)

Tom M. Mitchell: Artificial Intelligence and Human Brain Imaging. Canadian Conference on AI 2003: 7

Xuerui Wang, Rebecca A. Hutchinson, Tom M. Mitchell: Training fMRI Classifiers to Discriminate Cognitive States across Multiple Subjects. NIPS 2003

Tom M. Mitchell: Author's response to reviews of Machine Learning. Artif. Intell. 131(1-2): 223-225 (2001)

Yves Lespérance, Gerd Wagner, William P. Birmingham, Kurt D. Bollacker, Alexander Nareyek, J. Paul Walser, David W. Aha, Timothy W. Finin, Benjamin N. Grosof, Nathalie Japkowicz, Robert Holte, Lise Getoor, Carla P. Gomes, Holger H. Hoos, Alan C. Schultz, Miroslav Kubat, Tom M. Mitchell, Jörg Denzinger, Yolanda Gil, Karen L. Myers, Claudio Bettini, Angelo Montanari: AAAI 2000 Workshop Reports. AI Magazine 22(1): 127-136 (2001)

Tom M. Mitchell: Extracting targeted data from the web. KDD 2001: 3

Francisco Pereira, Marcel Adam Just, Tom M. Mitchell: Distinguishing Natural Language Processes on the Basis of fMRI-Measured Brain Activation. PKDD 2001: 374-385

Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Seán Slattery: Learning to construct knowledge bases from the World Wide Web. Artif. Intell. 118(1-2): 69-113 (2000)

Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell: Text Classification from Labeled and Unlabeled Documents using EM. Machine Learning 39(2/3): 103-134 (2000)

Seán Slattery, Tom M. Mitchell: Discovering Test Set Regularities in Relational Domains. ICML 2000: 895-902

Sebastian Thrun, Christos Faloutsos, Tom M. Mitchell, Larry A. Wasserman: Automated Learning and Discovery State-of-the-Art and Research Topics in a Rapidly Growing Field. AI Magazine 20(3): 78-82 (1999)

Tom M. Mitchell: Machine Learning and Data Mining. Commun. ACM 42(11): 30-36 (1999)

Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Seán Slattery: Learning to Extract Symbolic Knowledge from the World Wide Web. AAAI/IAAI 1998: 509-516

Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell: Learning to Classify Text from Labeled and Unlabeled Documents. AAAI/IAAI 1998: 792-799

Avrim Blum, Tom M. Mitchell: Combining Labeled and Unlabeled Sata with Co-Training. COLT 1998: 92-100

Andrew McCallum, Ronald Rosenfeld, Tom M. Mitchell, Andrew Y. Ng: Improving Text Classification by Shrinkage in a Hierarchy of Classes. ICML 1998: 359-367

Tom M. Mitchell: Machine learning. McGraw Hill series in computer science, McGraw-Hill 1997, isbn 978-0-07-042807-2, pp. I-XVII, 1-414

Tom M. Mitchell: Does Machine Learning Really Work? AI Magazine 18(3): 11-20 (1997)

Gregory F. Cooper, Constantin F. Aliferis, Richard Ambrosino, John M. Aronis, Bruce G. Buchanan, Rich Caruana, Michael J. Fine, Clark Glymour, Geoffrey J. Gordon, Barbara H. Hanusa, Janine E. Janosky, Christopher Meek, Tom M. Mitchell, Thomas S. Richardson, Peter Spirtes: An evaluation of machine-learning methods for predicting pneumonia mortality. Artificial Intelligence in Medicine 9(2): 107-138 (1997)

Tom M. Mitchell: Machine Learning Meets Natural Language. EPIA 1997: 391

Thorsten Joachims, Dayne Freitag, Tom M. Mitchell: Web Watcher: A Tour Guide for the World Wide Web. IJCAI (1) 1997: 770-777

Bart Selman, Rodney A. Brooks, Thomas L. Dean, Eric Horvitz, Tom M. Mitchell, Nils J. Nilsson: Challenge Problems for Artificial Intelligence (Panel Statements). AAAI/IAAI, Vol. 2 1996: 1340-1345

Sebastian Thrun, Tom M. Mitchell: Lifelong robot learning. Robotics and Autonomous Systems 15(1-2): 25-46 (1995)

Tom M. Mitchell: Machine Learning in the World Wide Web. ECML 1995: 32

Sebastian Thrun, Tom M. Mitchell: Learning One More Thing. IJCAI 1995: 1217-1225

Rich Caruana, Shumeet Baluja, Tom M. Mitchell: Using the Future to Sort Out the Present: Rankprop and Multitask Learning for Medical Risk Evaluation. NIPS 1995: 959-965

Tom M. Mitchell, Rich Caruana, Dayne Freitag, John P. McDermott, David Zabowski: Experience with a Learning Personal Assistant. Commun. ACM 37(7): 80-91 (1994)

Sridhar Mahadevan, Tom M. Mitchell, Jack Mostow, Louis I. Steinberg, Prasad Tadepalli: An Apprentice-Based Approach to Knowledge Acquisition. Artif. Intell. 64(1): 1-52 (1993)

Siegfried Bocionek, Tom M. Mitchell: Office Automation Systems that are "Programmed" by their Users. GI Jahrestagung 1993: 214-219

Tom M. Mitchell, Sebastian Thrun: Explanation Based Learning: A Comparison of Symbolic and Neural Network Approaches. ICML 1993: 197-204

Sebastian Thrun, Tom M. Mitchell: Integrating Inductive Neural Network Learning and Explanation-Based Learning. IJCAI 1993: 930-936

C. Lisa Dent, Jesus Boticario, John P. McDermott, Tom M. Mitchell, David Zabowski: A Personal Learning Apprentice. AAAI 1992: 96-103

Tom M. Mitchell, Sebastian Thrun: Explanation-Based Neural Network Learning for Robot Control. NIPS 1992: 287-294

Alan D. Christiansen, Matthew T. Mason, Tom M. Mitchell: Learning reliable manipulation strategies without initial physical models. Robotics and Autonomous Systems 8(1-2): 7-18 (1991)

Tom M. Mitchell: Plan-Then-Compile Architectures. SIGART Bulletin 2(4): 136-139 (1991)

Jeffrey C. Schlimmer, Tom M. Mitchell, John P. McDermott: Justification-Based Refinement of Expert Knowledge. Knowledge Discovery in Databases 1991: 397-410

Tom M. Mitchell: Personal Learning Apprentices. ISMIS 1991: 35-37

Tom M. Mitchell: Becoming Increasingly Reactive. AAAI 1990: 1051-1058

John Bares, Martial Hebert, Takeo Kanade, Eric Krotkov, Tom M. Mitchell, Reid G. Simmons, William Whittaker: Ambler: An Autonomous Rover for Planetary Exploration. IEEE Computer 22(6): 18-26 (1989)

Matthew T. Mason, Alan D. Christiansen, Tom M. Mitchell: Experiments in Robot Learning. ML 1989: 141-145

Jim Blythe, Tom M. Mitchell: On Becoming Reactive. ML 1989: 255-259

Howard E. Shrobe, Tom M. Mitchell, Reid G. Smith (Eds.): Proceedings of the 7th National Conference on Artificial Intelligence. St. Paul, MN, August 21-26, 1988. AAAI Press / The MIT Press 1988, isbn 0-262-51055-3

Tom M. Mitchell, Richard M. Keller, Smadar T. Kedar-Cabelli: Explanation-Based Generalization: A Unifying View. Machine Learning 1(1): 47-80 (1986)

Tom M. Mitchell, Louis I. Steinberg, Jeffrey S. Shulman: A Knowledge-Based Approach to Design. IEEE Trans. Pattern Anal. Mach. Intell. 7(5): 502-510 (1985)

Alexander Borgida, Tom M. Mitchell, Keith E. Williamson: Learning Improved Integrity Constraints and Schemes From Exceptions in Data and Knowledge Bases. On Knowledge Base Management Systems (Islamorada) 1985: 259-286

Tom M. Mitchell: Learning in Knowledge-Base Management Systems. On Knowledge Base Management Systems (Islamorada) 1985: 403-406

Tom M. Mitchell, Sridhar Mahadevan, Louis I. Steinberg: LEAP: A Learning Apprentice for VLSl Design. IJCAI 1985: 573-580

Reid G. Smith, Howard A. Winston, Tom M. Mitchell, Bruce G. Buchanan: Representation and Use of Explicit Justifications for Knowledge Base Refinements. IJCAI 1985: 673-680

Louis I. Steinberg, Tom M. Mitchell: A knowledge based approach to VLSI CAD the redesign system. DAC 1984: 412-418

Jaime G. Carbonell, Ryszard S. Michalski, Tom M. Mitchell: Machine Learning: A Historical and Methodological Analysis. AI Magazine 4(3): 69-79 (1983)

Tom M. Mitchell, Louis I. Steinberg, Smadar T. Kedar-Cabelli, Van E. Kelly, Jeffrey S. Shulman, Timothy Weinrich: An Intelligent Aid for Circuit Redesign. AAAI 1983: 274-278

Tom M. Mitchell: Learning and Problem Solving. IJCAI 1983: 1139-1151

Tom M. Mitchell: Generalization as Search. Artif. Intell. 18(2): 203-226 (1982)

Tom M. Mitchell: Artificial Intelligence Research at Rutgers. AI Magazine 3(2): 36-43 (1982)

Derek H. Sleeman, Pat Langley, Tom M. Mitchell: Learning from Solution Paths: An Approach to the Credit Assignment Problem. AI Magazine 3(2): 48-52 (1982)

Paul E. Utgoff, Tom M. Mitchell: Acquisition of Appropriate Bias for Inductive Concept Learning. AAAI 1982: 414-417

Tom M. Mitchell, Paul E. Utgoff, Bernard Nudel, Ranan B. Banerji: Learning Problem-Solving Heuristics Through Practice. IJCAI 1981: 127-134

Tom M. Mitchell, Louis I. Steinberg, Reid G. Smith, Pat Schooley, Howard Jacobs, Van E. Kelly: Representations for Reasoning about Digital Circuits. IJCAI 1981: 343-344

Tom M. Mitchell: An Analysis of Generalization as a Search Problem. IJCAI 1979: 577-582

Tom M. Mitchell: Version Spaces: A Candidate Elimination Approach to Rule Learning. IJCAI 1977: 305-310

Reid G. Smith, Tom M. Mitchell, R. A. Chestek, Bruce G. Buchanan: A Model for Learning Systems. IJCAI 1977: 338-343