| Year |
Citation |
Score |
| 2022 |
Toneva M, Mitchell TM, Wehbe L. Combining computational controls with natural text reveals aspects of meaning composition. Nature Computational Science. 2: 745-757. PMID 36777107 DOI: 10.1038/s43588-022-00354-6 |
0.757 |
|
| 2020 |
Sachan M, Dubey A, Hovy EH, Mitchell TM, Roth D, Xing EP. Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks Computational Linguistics. 45: 627-665. DOI: 10.1162/Coli_A_00360 |
0.318 |
|
| 2019 |
Fyshe A, Sudre G, Wehbe L, Rafidi N, Mitchell TM. The lexical semantics of adjective-noun phrases in the human brain. Human Brain Mapping. PMID 31313467 DOI: 10.1002/Hbm.24714 |
0.774 |
|
| 2019 |
Schwartz D, Mitchell T. Understanding language-elicited Arxiv: Computation and Language. DOI: 10.18653/V1/N19-1005 |
0.371 |
|
| 2019 |
Azaria A, Srivastava S, Krishnamurthy J, Labutov I, Mitchell TM. An agent for learning new natural language commands Autonomous Agents and Multi-Agent Systems. 34. DOI: 10.1007/S10458-019-09425-X |
0.352 |
|
| 2016 |
Papalexakis EE, Faloutsos C, Mitchell TM, Talukdar PP, Sidiropoulos ND, Murphy B. Turbo-SMT: Parallel Coupled Sparse Matrix-Tensor Factorizations and Applications. Statistical Analysis and Data Mining. 9: 269-290. PMID 27672406 DOI: 10.1002/Sam.11315 |
0.316 |
|
| 2015 |
Jordan MI, Mitchell TM. Machine learning: Trends, perspectives, and prospects. Science (New York, N.Y.). 349: 255-60. PMID 26185243 DOI: 10.1126/Science.Aaa8415 |
0.387 |
|
| 2015 |
Krishnamurthy J, Mitchell TM. Learning a Compositional Semantics for Freebase with an Open Predicate Vocabulary Transactions of the Association For Computational Linguistics. 3: 257-270. DOI: 10.1162/Tacl_A_00137 |
0.404 |
|
| 2015 |
Mitchell T, Cohen W, Hruschka E, Talukdar P, Betteridge J, Carlson A, Dalvi B, Gardner M, Kisiel. B, Krishnamurthy J, Lao N, Mazaitis K, Mohamed T, Nakashole N, Platanios E, et al. Never-Ending Learning Proceedings of the National Conference On Artificial Intelligence. 3: 2302-2310. DOI: 10.1145/3191513 |
0.708 |
|
| 2014 |
Just MA, Cherkassky VL, Buchweitz A, Keller TA, Mitchell TM. Identifying autism from neural representations of social interactions: neurocognitive markers of autism. Plos One. 9: e113879. PMID 25461818 DOI: 10.1371/Journal.Pone.0113879 |
0.365 |
|
| 2014 |
Wehbe L, Murphy B, Talukdar P, Fyshe A, Ramdas A, Mitchell T. Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses. Plos One. 9: e112575. PMID 25426840 DOI: 10.1371/Journal.Pone.0112575 |
0.789 |
|
| 2014 |
Kujala J, Sudre G, Vartiainen J, Liljeström M, Mitchell T, Salmelin R. Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing. Neuroimage. 92: 207-16. PMID 24518260 DOI: 10.1016/J.Neuroimage.2014.01.057 |
0.313 |
|
| 2012 |
Sudre G, Pomerleau D, Palatucci M, Wehbe L, Fyshe A, Salmelin R, Mitchell T. Tracking neural coding of perceptual and semantic features of concrete nouns. Neuroimage. 62: 451-63. PMID 22565201 DOI: 10.1016/J.Neuroimage.2012.04.048 |
0.774 |
|
| 2012 |
Buchweitz A, Shinkareva SV, Mason RA, Mitchell TM, Just MA. Identifying bilingual semantic neural representations across languages. Brain and Language. 120: 282-9. PMID 21978845 DOI: 10.1016/J.Bandl.2011.09.003 |
0.701 |
|
| 2012 |
Shinkareva SV, Malave VL, Just MA, Mitchell TM. Exploring commonalities across participants in the neural representation of objects. Human Brain Mapping. 33: 1375-83. PMID 21567662 DOI: 10.1002/Hbm.21296 |
0.68 |
|
| 2012 |
Murphy B, Talukdar PP, Mitchell T. Learning effective and interpretable semantic models using non-negative sparse embedding 24th International Conference On Computational Linguistics - Proceedings of Coling 2012: Technical Papers. 1933-1950. |
0.315 |
|
| 2011 |
Mitchell TM. From journal articles to computational models: a new automated tool. Nature Methods. 8: 627-8. PMID 21799495 DOI: 10.1038/Nmeth.1661 |
0.325 |
|
| 2011 |
Shinkareva SV, Malave VL, Mason RA, Mitchell TM, Just MA. Commonality of neural representations of words and pictures. Neuroimage. 54: 2418-25. PMID 20974270 DOI: 10.1016/J.Neuroimage.2010.10.042 |
0.692 |
|
| 2011 |
Chang KM, Mitchell T, Just MA. Quantitative modeling of the neural representation of objects: how semantic feature norms can account for fMRI activation. Neuroimage. 56: 716-27. PMID 20451625 DOI: 10.1016/J.Neuroimage.2010.04.271 |
0.403 |
|
| 2010 |
Just MA, Cherkassky VL, Aryal S, Mitchell TM. A neurosemantic theory of concrete noun representation based on the underlying brain codes. Plos One. 5: e8622. PMID 20084104 DOI: 10.1371/Journal.Pone.0008622 |
0.422 |
|
| 2010 |
Carlson A, Betteridge J, Wang RC, Hruschka ER, Mitchell TM. Coupled semi-supervised learning for information extraction Wsdm 2010 - Proceedings of the 3rd Acm International Conference On Web Search and Data Mining. 101-110. DOI: 10.1145/1718487.1718501 |
0.489 |
|
| 2010 |
Carlson A, Betteridge J, Kisiel B, Settles B, Hruschka ER, Mitchell TM. Toward an architecture for never-ending language learning Proceedings of the National Conference On Artificial Intelligence. 3: 1306-1313. |
0.515 |
|
| 2009 |
Mitchell TM. Computer science. Mining our reality. Science (New York, N.Y.). 326: 1644-5. PMID 20019279 DOI: 10.1126/Science.1174459 |
0.325 |
|
| 2009 |
Hutchinson RA, Niculescu RS, Keller TA, Rustandi I, Mitchell TM. Modeling fMRI data generated by overlapping cognitive processes with unknown onsets using Hidden Process Models. Neuroimage. 46: 87-104. PMID 19457397 DOI: 10.1016/J.Neuroimage.2009.01.025 |
0.733 |
|
| 2009 |
Pereira F, Mitchell T, Botvinick M. Machine learning classifiers and fMRI: a tutorial overview. Neuroimage. 45: S199-209. PMID 19070668 DOI: 10.1016/J.Neuroimage.2008.11.007 |
0.714 |
|
| 2009 |
Mitchell TM, Carlson A, Hruschka E, Wang R. Populating the semantic web by macro-reading internet text Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5823: 998-1002. DOI: 10.1007/978-3-642-04930-9_66 |
0.426 |
|
| 2009 |
Palatucci M, Pomerleau D, Hinton G, Mitchell TM. Zero-shot learning with semantic output codes Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 1410-1418. |
0.773 |
|
| 2008 |
Mitchell TM, Shinkareva SV, Carlson A, Chang KM, Malave VL, Mason RA, Just MA. Predicting human brain activity associated with the meanings of nouns. Science (New York, N.Y.). 320: 1191-5. PMID 18511683 DOI: 10.1126/Science.1152876 |
0.753 |
|
| 2008 |
Shinkareva SV, Mason RA, Malave VL, Wang W, Mitchell TM, Just MA. Using FMRI brain activation to identify cognitive states associated with perception of tools and dwellings. Plos One. 3: e1394. PMID 18167553 DOI: 10.1371/Journal.Pone.0001394 |
0.679 |
|
| 2007 |
Niculescu RS, Mitchell TM, Rao RB. Modeling the fMRI signal via Hierarchical Clustered Hidden Process Models. Amia ... Annual Symposium Proceedings / Amia Symposium. Amia Symposium. 558-62. PMID 18693898 |
0.762 |
|
| 2007 |
Niculescu RS, Mitchell TM, Rao RB. A theoretical framework for learning Bayesian networks with parameter inequality constraints Ijcai International Joint Conference On Artificial Intelligence. 155-160. |
0.732 |
|
| 2007 |
Palatucci M, Mitchell TM. Classification in very high dimensional problems with handfuls of examples Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4702: 212-223. |
0.739 |
|
| 2006 |
Chen X, Pereira F, Lee W, Strother S, Mitchell T. Exploring predictive and reproducible modeling with the single-subject FIAC dataset. Human Brain Mapping. 27: 452-61. PMID 16565951 DOI: 10.1002/Hbm.20243 |
0.566 |
|
| 2006 |
Hutchinson RA, Mitchell TM, Rustandi I. Hidden process models Acm International Conference Proceeding Series. 148: 433-440. DOI: 10.1145/1143844.1143899 |
0.73 |
|
| 2006 |
Niculescu RS, Mitchell TM, Rao RB. Bayesian network learning with parameter constraints Journal of Machine Learning Research. 7: 1357-1383. |
0.731 |
|
| 2005 |
Cooper GF, Abraham V, Aliferis CF, Aronis JM, Buchanan BG, Caruana R, Fine MJ, Janosky JE, Livingston G, Mitchell T, Monti S, Spirtes P. Predicting dire outcomes of patients with community acquired pneumonia. Journal of Biomedical Informatics. 38: 347-66. PMID 16198995 DOI: 10.1016/J.Jbi.2005.02.005 |
0.624 |
|
| 2005 |
Mitchell TM, Levesque HJ. The 2005 AAAI Classic Paper Awards Ai Magazine. 26: 98-99. DOI: 10.1609/Aimag.V26I4.1853 |
0.343 |
|
| 2005 |
Niculescu RS, Mitchell TM, Bharat Rao R. Exploiting parameter related domain knowledge for learning in graphical models Proceedings of the 2005 Siam International Conference On Data Mining, Sdm 2005. 310-321. |
0.744 |
|
| 2005 |
Neill DB, Moore AW, Pereira F, Mitchell T. Detecting significant multidimensional spatial clusters Advances in Neural Information Processing Systems. |
0.369 |
|
| 2004 |
Mitchell TM, Hutchinson R, Niculescu RS, Pereira F, Wang X, Just M, Newman S. Learning to decode cognitive states from brain images Machine Learning. 57: 145-175. DOI: 10.1023/B:Mach.0000035475.85309.1B |
0.801 |
|
| 2004 |
Wang X, Hutchinson R, Mitchell TM. Training fMRI classifiers to discriminate cognitive states across multiple subjects Advances in Neural Information Processing Systems. |
0.485 |
|
| 2003 |
Mitchell TM, Hutchinson R, Just MA, Niculescu RS, Pereira F, Wang X. Classifying instantaneous cognitive states from FMRI data. Amia ... Annual Symposium Proceedings / Amia Symposium. Amia Symposium. 465-9. PMID 14728216 |
0.783 |
|
| 2003 |
Mitchell TM. Artificial intelligence and human brain imaging Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2671: 7. DOI: 10.1007/3-540-44886-1_2 |
0.328 |
|
| 2001 |
Lesperance Y, Wagnerg G, Birmingham W, Bollacker K, Nareyek A, Walser JP, Aha D, Finin T, Grosof B, Japkowicz N, Holte R, Getoor L, Gomes CP, Hoos HH, Schultz AC, ... ... Mitchell T, et al. AAAI 2000 workshop reports Ai Magazine. 22: 127-135. DOI: 10.1609/Aimag.V22I1.1552 |
0.392 |
|
| 2001 |
Mitchell T. Author's response to reviews of Machine learning Artificial Intelligence. 131: 223-225. DOI: 10.1016/S0004-3702(01)00142-4 |
0.329 |
|
| 2001 |
Pereira F, Just M, Mitchell T. Distinguishing natural language processes on the basis of fMRI-measured brain activation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2168: 374-385. |
0.499 |
|
| 2000 |
Nigam K, Mccallum AK, Thrun S, Mitchell T. Text classification from labeled and unlabeled documents using EM Machine Learning. 39: 103-134. DOI: 10.1023/A:1007692713085 |
0.675 |
|
| 2000 |
Nigam K, Mccallum AK, Thrun S, Mitchell T. Machine Learning. 39: 103-134. DOI: 10.1023/A:1007692713085 |
0.613 |
|
| 2000 |
Craven M, Dipasquo D, Freitag D, McCallum A, Mitchell T, Nigam K, Slattery S. Learning to construct knowledge bases from the World Wide Web Artificial Intelligence. 118: 69-113. DOI: 10.1016/S0004-3702(00)00004-7 |
0.378 |
|
| 1999 |
Thrun S, Faloutsos C, Mitchell TM, Wasserman LA. Automated Learning and Discovery State-of-the-Art and Research Topics in a Rapidly Growing Field Ai Magazine. 20: 78-82. DOI: 10.1609/Aimag.V20I3.1468 |
0.658 |
|
| 1999 |
Mitchell TM. Machine Learning and Data Mining Communications of the Acm. 42: 31-36. DOI: 10.1145/319382.319388 |
0.377 |
|
| 1997 |
Cooper GF, Aliferis CF, Ambrosino R, Aronis J, Buchanan BG, Caruana R, Fine MJ, Glymour C, Gordon G, Hanusa BH, Janosky JE, Meek C, Mitchell T, Richardson T, Spirtes P. An evaluation of machine-learning methods for predicting pneumonia mortality. Artificial Intelligence in Medicine. 9: 107-38. PMID 9040894 DOI: 10.1016/S0933-3657(96)00367-3 |
0.707 |
|
| 1997 |
Mitchell TM. Does machine learning really work? Ai Magazine. 18: 11-20. DOI: 10.1609/Aimag.V18I3.1303 |
0.394 |
|
| 1995 |
Thrun S, Mitchell TM. Lifelong robot learning Robotics and Autonomous Systems. 15: 25-46. DOI: 10.1016/0921-8890(95)00004-Y |
0.668 |
|
| 1994 |
Mitchell T, Carahuana R, Freitag D, McDermott J, Zabowski D. Experience with a learning personal assistant Communications of the Acm. 37: 81-91. DOI: 10.1145/176789.176798 |
0.337 |
|
| 1993 |
Mahadevan S, Mitchell TM, Mostow J, Steinberg L, Tadepalli PV. An apprentice-based approach to knowledge acquisition Artificial Intelligence. 64: 1-52. DOI: 10.1016/0004-3702(93)90059-K |
0.39 |
|
| 1991 |
Christiansen AD, Mason MT, Mitchell TM. Learning reliable manipulation strategies without initial physical models Robotics and Autonomous Systems. 8: 7-18. DOI: 10.1016/0921-8890(91)90011-9 |
0.359 |
|
| 1990 |
Mitchell TM, Mahadevan S, Steinberg LI. LEAP: a learning apprentice for VLSI design Machine Learning. 271-301. DOI: 10.1016/B978-0-08-051055-2.50016-X |
0.371 |
|
| 1989 |
Tanaka T, Mitchell TM. Embedding learning in a general frame-based architecture . 77-84. DOI: 10.1142/S0218001490000101 |
0.394 |
|
| 1986 |
Mitchell TM, Keller RM, Kedar-Cabelli ST. Explanation-Based Generalization: A Unifying View Machine Learning. 1: 47-80. DOI: 10.1023/A:1022691120807 |
0.342 |
|
| 1983 |
Carbonell JG, Michalski RS, Mitchell TM. Machine Learning: A Historical and Methodological Analysis Ai Magazine. 4: 69-79. DOI: 10.1609/Aimag.V4I3.406 |
0.404 |
|
| 1982 |
Sleeman DH, Langley P, Mitchell TM. Learning from Solution Paths: An Approach to the Credit Assignment Problem Ai Magazine. 3: 48-52. DOI: 10.1609/Aimag.V3I2.372 |
0.375 |
|
| 1982 |
Mitchell TM. Generalization as search Artificial Intelligence. 18: 203-226. DOI: 10.1016/0004-3702(82)90040-6 |
0.32 |
|
| 1977 |
Buchanan BG, Mitchell TM. Model-directed learning of production rules Intelligence\/Sigart Bulletin. 63: 44-44. DOI: 10.1145/1045343.1045371 |
0.647 |
|
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