99Scoup-SMT: Scalable Coupled Sparse Matrix-Tensor Factorization. Evangelos E. Papalexakis, Tom M. Mitchell, Nicholas D. Sidiropoulos, Christos Faloutsos, Partha Pratim Talukdar, Brian Murphy. CoRR (abs/1302.7043) (2013). Web SearchBibTeXDownload
98Never Ending Learning. Tom M. Mitchell. ECAI 2012, 5. Web SearchBibTeXDownload
97Hierarchical Latent Dictionaries for Models of Brain Activation. Alona Fyshe, Emily B. Fox, David B. Dunson, Tom M. Mitchell. Journal of Machine Learning Research - Proceedings Track (22): 409-421 (2012). Web SearchBibTeXDownload
96Tracking neural coding of perceptual and semantic features of concrete nouns. Gustavo Sudre, Dean Pomerleau, Mark Palatucci, Leila Wehbe, Alona Fyshe, Riitta Salmelin, Tom M. Mitchell. NeuroImage (62): 451-463 (2012). Web SearchBibTeXDownload
95Random Walk Inference and Learning in A Large Scale Knowledge Base. Ni Lao, Tom M. Mitchell, William W. Cohen. EMNLP 2011, 529-539. Web SearchBibTeXDownload
94Discovering Relations between Noun Categories. Thahir Mohamed, Estevam R. Hruschka Jr., Tom M. Mitchell. EMNLP 2011, 1447-1455. Web SearchBibTeXDownload
93Neural Representations of Word Meanings. Tom M. Mitchell. INTERSPEECH 2011. Web SearchBibTeXDownload
92Quantitative modeling of the neural representation of objects: How semantic feature norms can account for fMRI activation. Kai-min Kevin Chang, Tom M. Mitchell, Marcel Adam Just. NeuroImage (56): 716-727 (2011). Web SearchBibTeXDownload
91Commonality of neural representations of words and pictures. Svetlana V. Shinkareva, Vicente L. Malave, Robert A. Mason, Tom M. Mitchell, Marcel Adam Just. NeuroImage (54): 2418-2425 (2011). Web SearchBibTeXDownload
90Toward an Architecture for Never-Ending Language Learning. Andrew Carlson, Justin Betteridge, Bryan Kisiel, Burr Settles, Estevam R. Hruschka Jr., Tom M. Mitchell. AAAI 2010. Web SearchBibTeXDownload
89Learning to Tag from Open Vocabulary Labels. Edith Law, Burr Settles, Tom M. Mitchell. ECML/PKDD (2) 2010, 211-226. Web SearchBibTeXDownload
88Coupled semi-supervised learning for information extraction. Andrew Carlson, Justin Betteridge, Richard C. Wang, Estevam R. Hruschka Jr., Tom M. Mitchell. WSDM 2010, 101-110. Web SearchBibTeXDownload
87Toward Mixed-Initiative Email Clustering. Yifen Huang, Tom M. Mitchell. AAAI Spring Symposium: Agents that Learn from Human Teachers 2009, 71-78. Web SearchBibTeXDownload
86Toward Never Ending Language Learning. Justin Betteridge, Andrew Carlson, Sue Ann Hong, Estevam R. Hruschka Jr., Edith L. M. Law, Tom M. Mitchell, Sophie H. Wang. AAAI Spring Symposium: Learning by Reading and Learning to Read 2009, 1-2. Web SearchBibTeXDownload
85Quantitative modeling of the neural representation of adjective-noun phrases to account for fMRI activation. Kai-min K. Chang, Vladimir Cherkassky, Tom M. Mitchell, Marcel Adam Just. ACL/IJCNLP 2009, 638-646. Web SearchBibTeXDownload
84Populating the Semantic Web by Macro-reading Internet Text. Tom M. Mitchell, Justin Betteridge, Andrew Carlson, Estevam R. Hruschka Jr., Richard C. Wang. International Semantic Web Conference 2009, 998-1002. Web SearchBibTeXDownload
83Modeling fMRI data generated by overlapping cognitive processes with unknown onsets using Hidden Process Models. Rebecca A. Hutchinson, Radu Stefan Niculescu, Timothy A. Keller, Indrayana Rustandi, Tom M. Mitchell. NeuroImage (46): 87-104 (2009). Web SearchBibTeXDownload
82Zero-shot Learning with Semantic Output Codes. Mark Palatucci, Dean Pomerleau, Geoffrey E. Hinton, Tom M. Mitchell. NIPS 2009, 1410-1418. Web SearchBibTeXDownload
81Computational Models of Neural Representations in the Human Brain. Tom M. Mitchell. ALT 2008, 5-6. Web SearchBibTeXDownload
80In Honor of Marvin Minsky's Contributions on his 80th Birthday. Danny Hillis, John McCarthy, Tom M. Mitchell, Erik T. Mueller, Doug Riecken, Aaron Sloman, Patrick Henry Winston. AI Magazine (28): 103-110 (2007). Web SearchBibTeXDownload
79Learning, Information Extraction and the Web. Tom M. Mitchell. ECML/PKDD 2007, 1. Web SearchBibTeXDownload
78A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints. Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat Rao. IJCAI 2007, 155-160. Web SearchBibTeXDownload
77Feature selection for grasp recognition from optical markers. Lillian Y. Chang, Nancy S. Pollard, Tom M. Mitchell, Eric P. Xing. IROS 2007, 2944-2950. Web SearchBibTeXDownload
76Classification in Very High Dimensional Problems with Handfuls of Examples. Mark Palatucci, Tom M. Mitchell. PKDD 2007, 212-223. Web SearchBibTeXDownload
75Extracting Knowledge about Users' Activities from Raw Workstation Contents. Tom M. Mitchell, Sophie H. Wang, Yifen Huang, Adam Cheyer. AAAI 2006, 181-186. Web SearchBibTeXDownload
74Hidden process models. Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rustandi. ICML 2006, 433-440. Web SearchBibTeXDownload
73Bayesian Network Learning with Parameter Constraints. Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat Rao. Journal of Machine Learning Research (7): 1357-1383 (2006). Web SearchBibTeXDownload
72Text clustering with extended user feedback. Yifen Huang, Tom M. Mitchell. SIGIR 2006, 413-420. Web SearchBibTeXDownload
71The 2005 AAAI Classic Paper Awards. Tom M. Mitchell, Hector J. Levesque. AI Magazine (26): 98-99 (2005). Web SearchBibTeXDownload
70Learning Topic-Based Mixture Models for Factored Classification. Qiong Chen, Tom M. Mitchell. CIMCA/IAWTIC 2005, 25-31. Web SearchBibTeX
69Predicting dire outcomes of patients with community acquired pneumonia. 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. Journal of Biomedical Informatics (38): 347-366 (2005). Web SearchBibTeXDownload
68Machine Learning for Analyzing Human Brain Function. Tom M. Mitchell. PAKDD 2005, 1. Web SearchBibTeXDownload
67Exploiting Parameter Related Domain Knowledge for Learning in Graphical Models. Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat Rao. SDM 2005. Web SearchBibTeX
66Inferring Ongoing Activities of Workstation Users by Clustering Email. Yifen Huang, Dinesh Govindaraju, Tom M. Mitchell, Vitor Rocha de Carvalho, William W. Cohen. CEAS 2004. Web SearchBibTeXDownload
65Learning to Classify Email into ``Speech Acts''. William W. Cohen, Vitor R. Carvalho, Tom M. Mitchell. EMNLP 2004, 309-316. Web SearchBibTeXDownload
64Learning to Decode Cognitive States from Brain Images. Tom M. Mitchell, Rebecca Hutchinson, Radu Stefan Niculescu, Francisco Pereira, Xuerui Wang, Marcel Just, Sharlene Newman. Machine Learning (57): 145-175 (2004). Web SearchBibTeXDownload
63Detecting Significant Multidimensional Spatial Clusters. Daniel B. Neill, Andrew W. Moore, Francisco Pereira, Tom M. Mitchell. NIPS 2004. Web SearchBibTeXDownload
62Intelligent Workstation Agents and Unstructured Workstation Data. Tom M. Mitchell. Web Intelligence 2004, 6. Web SearchBibTeXDownload
61In Memoriam: Charles Rosen, Norman Nielsen, and Saul Amarel. Peter E. Hart, Nils J. Nilsson, Ray Perrault, Tom M. Mitchell, Casimir A. Kulikowski. AI Magazine (24): 6-12 (2003). Web SearchBibTeXDownload
60Artificial Intelligence and Human Brain Imaging. Tom M. Mitchell. Canadian Conference on AI 2003, 7. Web SearchBibTeXDownload
59AI Matures and Flourishes in North America. David Mike Hamilton, Tom M. Mitchell, Carol McKenna Hamilton. IEEE Intelligent Systems (18): 87 (2003). Web SearchBibTeXDownload
58Training fMRI Classifiers to Discriminate Cognitive States across Multiple Subjects. Xuerui Wang, Rebecca Hutchinson, Tom M. Mitchell. NIPS 2003. Web SearchBibTeXDownload
57AAAI 2000 Workshop Reports. 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. AI Magazine (22): 127-136 (2001). Web SearchBibTeXDownload
56Author's response to reviews of Machine Learning. Tom M. Mitchell. Artif. Intell. (131): 223-225 (2001). Web SearchBibTeXDownload
55Extracting targeted data from the web. Tom M. Mitchell. KDD 2001, 3. Web SearchBibTeXDownload
54Distinguishing Natural Language Processes on the Basis of fMRI-Measured Brain Activation. Francisco Pereira, Marcel Adam Just, Tom M. Mitchell. PKDD 2001, 374-385. Web SearchBibTeXDownload
53Learning to construct knowledge bases from the World Wide Web. Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Seán Slattery. Artif. Intell. (118): 69-113 (2000). Web SearchBibTeXDownload
52Discovering Test Set Regularities in Relational Domains. Seán Slattery, Tom M. Mitchell. ICML 2000, 895-902. Web SearchBibTeX
51Text Classification from Labeled and Unlabeled Documents using EM. Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell. Machine Learning (39): 103-134 (2000). Web SearchBibTeXDownload
50Automated Learning and Discovery State-of-the-Art and Research Topics in a Rapidly Growing Field. Sebastian Thrun, Christos Faloutsos, Tom M. Mitchell, Larry A. Wasserman. AI Magazine (20): 78-82 (1999). Web SearchBibTeXDownload
49Automated Learning and Discovery Stat-Of-The-Art and Research Topics in a Rapidly Growing Field. Sebastian Thrun, Christos Faloutsos, Tom M. Mitchell, Larry A. Wasserman. AI Magazine (20): 78-82 (1999). Web SearchBibTeX
48Machine Learning and Data Mining. Tom M. Mitchell, Attilio Giordana, Lorenza Saitta. Commun. ACM (42): 30-36 (1999). Web SearchBibTeXDownload
47Learning to Classify Text from Labeled and Unlabeled Documents. Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell. AAAI/IAAI 1998, 792-799. Web SearchBibTeXDownload
46Learning to Extract Symbolic Knowledge from the World Wide Web. Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Seán Slattery. AAAI/IAAI 1998, 509-516. Web SearchBibTeXDownload
45Combining Labeled and Unlabeled Sata with Co-Training. Avrim Blum, Tom M. Mitchell. COLT 1998, 92-100. Web SearchBibTeXDownload
44Improving Text Classification by Shrinkage in a Hierarchy of Classes. Andrew McCallum, Ronald Rosenfeld, Tom M. Mitchell, Andrew Y. Ng. ICML 1998, 359-367. Web SearchBibTeX
43Does Machine Learning Really Work?. Tom M. Mitchell. AI Magazine (18): 11-20 (1997). Web SearchBibTeXDownload
42An evaluation of machine-learning methods for predicting pneumonia mortality. 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. Artificial Intelligence in Medicine (9): 107-138 (1997). Web SearchBibTeXDownload
41Machine Learning Meets Natural Language. Tom M. Mitchell. EPIA 1997, 391. Web SearchBibTeXDownload
40Web Watcher: A Tour Guide for the World Wide Web. Thorsten Joachims, Dayne Freitag, Tom M. Mitchell. IJCAI (1) 1997, 770-777. Web SearchBibTeX
39Challenge Problems for Artificial Intelligence (Panel Statements). Bart Selman, Rodney A. Brooks, Thomas Dean, Eric Horvitz, Tom M. Mitchell, Nils J. Nilsson. AAAI/IAAI, Vol. 2 1996, 1340-1345. Web SearchBibTeXDownload
38Machine Learning in the World Wide Web. Tom M. Mitchell. ECML 1995, 32. Web SearchBibTeXDownload
37Learning One More Thing. Sebastian Thrun, Tom M. Mitchell. IJCAI 1995, 1217-1225. Web SearchBibTeX
36Using the Future to Sort Out the Present: Rankprop and Multitask Learning for Medical Risk Evaluation. Rich Caruana, Shumeet Baluja, Tom M. Mitchell. NIPS 1995, 959-965. Web SearchBibTeXDownload
35Lifelong robot learning. Sebastian Thrun, Tom M. Mitchell. Robotics and Autonomous Systems (15): 25-46 (1995). Web SearchBibTeXDownload
34Experience with a Learning Personal Assistant. Tom M. Mitchell, Rich Caruana, Dayne Freitag, John P. McDermott, David Zabowski. Commun. ACM (37): 80-91 (1994). Web SearchBibTeXDownload
33An Apprentice-Based Approach to Knowledge Acquisition. Sridhar Mahadevan, Tom M. Mitchell, Jack Mostow, Louis I. Steinberg, Prasad Tadepalli. Artif. Intell. (64): 1-52 (1993). Web SearchBibTeXDownload
32Office Automation Systems that are "Programmed" by their Users. Siegfried Bocionek, Tom M. Mitchell. GI Jahrestagung 1993, 214-219. Web SearchBibTeX
31Explanation Based Learning: A Comparison of Symbolic and Neural Network Approaches. Tom M. Mitchell, Sebastian Thrun. ICML 1993, 197-204. Web SearchBibTeX
30Integrating Inductive Neural Network Learning and Explanation-Based Learning. Sebastian Thrun, Tom M. Mitchell. IJCAI 1993, 930-936. Web SearchBibTeX
29A Personal Learning Apprentice. C. Lisa Dent, Jesus Boticario, John P. McDermott, Tom M. Mitchell, David Zabowski. AAAI 1992, 96-103. Web SearchBibTeXDownload
28Explanation-Based Neural Network Learning for Robot Control. Tom M. Mitchell, Sebastian Thrun. NIPS 1992, 287-294. Web SearchBibTeXDownload
27Personal Learning Apprentices. Tom M. Mitchell. ISMIS 1991, 35-37. Web SearchBibTeXDownload
26Justification-Based Refinement of Expert Knowledge. Jeffrey C. Schlimmer, Tom M. Mitchell, John P. McDermott. Knowledge Discovery in Databases 1991, 397-410. Web SearchBibTeX
25Learning reliable manipulation strategies without initial physical models. Alan D. Christiansen, Matthew T. Mason, Tom M. Mitchell. Robotics and Autonomous Systems (8): 7-18 (1991). Web SearchBibTeXDownload
24Plan-Then-Compile Architectures. Tom M. Mitchell. SIGART Bulletin (2): 136-139 (1991). Web SearchBibTeXDownload
23Becoming Increasingly Reactive. Tom M. Mitchell. AAAI 1990, 1051-1058. Web SearchBibTeXDownload
22Ambler: An Autonomous Rover for Planetary Exploration. John Bares, Martial Hebert, Takeo Kanade, Eric Krotkov, Tom M. Mitchell, Reid G. Simmons, William Whittaker. IEEE Computer (22): 18-26 (1989). Web SearchBibTeXDownload
21Experiments in Robot Learning. Matthew T. Mason, Alan D. Christiansen, Tom M. Mitchell. ML 1989, 141-145. Web SearchBibTeX
20On Becoming Reactive. Jim Blythe, Tom M. Mitchell. ML 1989, 255-259. Web SearchBibTeX
19Explanation-Based Generalization: A Unifying View. Tom M. Mitchell, Richard M. Keller, Smadar T. Kedar-Cabelli. Machine Learning (1): 47-80 (1986). Web SearchBibTeXDownload
18A Knowledge-Based Approach to Design. Tom M. Mitchell, Louis I. Steinberg, Jeffrey S. Shulman. IEEE Trans. Pattern Anal. Mach. Intell. (7): 502-510 (1985). Web SearchBibTeXDownload
17LEAP: A Learning Apprentice for VLSl Design. Tom M. Mitchell, Sridhar Mahadevan, Louis I. Steinberg. IJCAI 1985, 573-580. Web SearchBibTeX
16Representation and Use of Explicit Justifications for Knowledge Base Refinements. Reid G. Smith, Howard A. Winston, Tom M. Mitchell, Bruce G. Buchanan. IJCAI 1985, 673-680. Web SearchBibTeX
15Learning Improved Integrity Constraints and Schemes From Exceptions in Data and Knowledge Bases. Alexander Borgida, Tom M. Mitchell, Keith E. Williamson. On Knowledge Base Management Systems (Islamorada) 1985, 259-286. Web SearchBibTeX
14Learning in Knowledge-Base Management Systems. Tom M. Mitchell. On Knowledge Base Management Systems (Islamorada) 1985, 403-406. Web SearchBibTeX
13A knowledge based approach to VLSI CAD the redesign system. Louis I. Steinberg, Tom M. Mitchell. DAC 1984, 412-418. Web SearchBibTeXDownload
12An Intelligent Aid for Circuit Redesign. Tom M. Mitchell, Louis I. Steinberg, Smadar T. Kedar-Cabelli, Van E. Kelly, Jeffrey Shulman, Timothy Weinrich. AAAI 1983, 274-278. Web SearchBibTeXDownload
11Machine Learning: A Historical and Methodological Analysis. Jaime G. Carbonell, Ryszard S. Michalski, Tom M. Mitchell. AI Magazine (4): 69-79 (1983). Web SearchBibTeXDownload
10Learning and Problem Solving. Tom M. Mitchell. IJCAI 1983, 1139-1151. Web SearchBibTeX
9Acquisition of Appropriate Bias for Inductive Concept Learning. Paul E. Utgoff, Tom M. Mitchell. AAAI 1982, 414-417. Web SearchBibTeXDownload
8Artificial Intelligence Research at Rutgers. Tom M. Mitchell. AI Magazine (3): 36-43 (1982). Web SearchBibTeXDownload
7Learning from Solution Paths: An Approach to the Credit Assignment Problem. Derek H. Sleeman, Pat Langley, Tom M. Mitchell. AI Magazine (3): 48-52 (1982). Web SearchBibTeXDownload
6Generalization as Search. Tom M. Mitchell. Artif. Intell. (18): 203-226 (1982). Web SearchBibTeXDownload
5Representations for Reasoning about Digital Circuits. Tom M. Mitchell, Louis I. Steinberg, Reid G. Smith, Pat Schooley, Howard Jacobs, Van E. Kelly. IJCAI 1981, 343-344. Web SearchBibTeX
4Learning Problem-Solving Heuristics Through Practice. Tom M. Mitchell, Paul E. Utgoff, Bernard Nudel, Ranan B. Banerji. IJCAI 1981, 127-134. Web SearchBibTeX
3An Analysis of Generalization as a Search Problem. Tom M. Mitchell. IJCAI 1979, 577-582. Web SearchBibTeX
2A Model for Learning Systems. Reid G. Smith, Tom M. Mitchell, R. A. Chestek, Bruce G. Buchanan. IJCAI 1977, 338-343. Web SearchBibTeX
1Version Spaces: A Candidate Elimination Approach to Rule Learning. Tom M. Mitchell. IJCAI 1977, 305-310. Web SearchBibTeX
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