Version Spaces: A Candidate Elimination Approach to Rule Learning. - Tom M. Mitchell (IJCAI, 1977)

A Model for Learning Systems. - Reid G. Smith; Tom M. Mitchell; R. A. Chestek; Bruce G. Buchanan (IJCAI, 1977)

Model-directed learning of production rules. - Bruce G. Buchanan; Tom M. Mitchell (SIGART Newsl., 1977)

An Analysis of Generalization as a Search Problem. - Tom M. Mitchell (IJCAI, 1979)

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

Learning Problem-Solving Heuristics Through Practice. - Tom M. Mitchell; Paul E. Utgoff; Bernard Nudel; Ranan B. Banerji (IJCAI, 1981)

Acquisition of Appropriate Bias for Inductive Concept Learning. - Paul E. Utgoff; Tom M. Mitchell (AAAI, 1982)

Generalization as Search. - Tom M. Mitchell (Artif. Intell., 1982)

Artificial Intelligence Research at Rutgers. - Tom M. Mitchell (AI Mag., 1982)

Learning from Solution Paths: An Approach to the Credit Assignment Problem. - Derek H. Sleeman; Pat Langley; Tom M. Mitchell (AI Mag., 1982)

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

Learning and Problem Solving. - Tom M. Mitchell (IJCAI, 1983)

Machine Learning: A Historical and Methodological Analysis. - Jaime G. Carbonell; Ryszard S. Michalski; Tom M. Mitchell (AI Mag., 1983)

A knowledge based approach to VLSI CAD the redesign system. - Louis I. Steinberg; Tom M. Mitchell (DAC, 1984)

Learning 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)

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

LEAP: A Learning Apprentice for VLSI Design. - Tom M. Mitchell; Sridhar Mahadevan; Louis I. Steinberg (IJCAI, 1985)

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

The Redesign System: A Knowledge-Based Approach to VLSI CAD. - Louis I. Steinberg; Tom M. Mitchell (IEEE Des. Test, 1985)

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

Explanation-Based Generalization: A Unifying View. - Tom M. Mitchell; Richard M. Keller; Smadar T. Kedar-Cabelli (Mach. Learn., 1986)

On Becoming Reactive. - Jim Blythe; Tom M. Mitchell (ML, 1989)

Experiments in Robot Learning. - Matthew T. Mason; Alan D. Christiansen; Tom M. Mitchell (ML, 1989)

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

Becoming Increasingly Reactive. - Tom M. Mitchell (AAAI, 1990)

Embedding Learning in a General Frame-Based Architecture. - Toshikazu Tanaka; Tom M. Mitchell (Int. J. Pattern Recognit. Artif. Intell., 1990)

Justification-Based Refinement of Expert Knowledge. - Jeffrey C. Schlimmer; Tom M. Mitchell; John P. McDermott (Knowledge Discovery in Databases, 1991)

Personal Learning Apprentices. - Tom M. Mitchell (ISMIS, 1991)

Learning reliable manipulation strategies without initial physical models. - Alan D. Christiansen; Matthew T. Mason; Tom M. Mitchell (Robotics Auton. Syst., 1991)

Plan-Then-Compile Architectures. - Tom M. Mitchell (SIGART Bull., 1991)

A Personal Learning Apprentice. - C. Lisa Dent; Jesus Boticario; John P. McDermott; Tom M. Mitchell; David Zabowski (AAAI, 1992)

Explanation-Based Neural Network Learning for Robot Control. - Tom M. Mitchell; Sebastian Thrun (NIPS, 1992)

Office Automation Systems that are "Programmed" by their Users. - Siegfried Bocionek; Tom M. Mitchell (GI Jahrestagung, 1993)

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

Integrating Inductive Neural Network Learning and Explanation-Based Learning. - Sebastian Thrun; Tom M. Mitchell (IJCAI, 1993)

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

The engineering design research center of Carnegie Mellon University. - Georgette H. Demes; Steven J. Fenves; Ignacio E. Grossmann; Chris T. Hendrickson; Tom M. Mitchell; Friedrich B. Prinz; Daniel P. Siewiorek; Eswaran Subrahmanian; Sarosh Talukdar; Arthur Westerberg (Proc. IEEE, 1993)

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

Machine Learning in the World Wide Web. - Tom M. Mitchell (ECML, 1995)

Learning One More Thing. - Sebastian Thrun; Tom M. Mitchell (IJCAI, 1995)

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

Lifelong robot learning. - Sebastian Thrun; Tom M. Mitchell (Robotics Auton. Syst., 1995)

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

Machine learning, International Edition. - Tom M. Mitchell (McGraw-Hill, 1997)

Machine Learning Meets Natural Language. - Tom M. Mitchell (EPIA, 1997)

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

Does Machine Learning Really Work? - Tom M. Mitchell (AI Mag., 1997)

An 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; et al. (Artif. Intell. Medicine, 1997)

Learning 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)

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

Combining Labeled and Unlabeled Data with Co-Training. - Avrim Blum; Tom M. Mitchell (COLT, 1998)

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

Automated 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 Mag., 1999)

Machine Learning and Data Mining. - Tom M. Mitchell (Commun. ACM, 1999)

Discovering Test Set Regularities in Relational Domains. - Seán Slattery; Tom M. Mitchell (ICML, 2000)

Learning 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., 2000)

Text Classification from Labeled and Unlabeled Documents using EM. - Kamal Nigam; Andrew Kachites McCallum; Sebastian Thrun; Tom M. Mitchell (Mach. Learn., 2000)

Extracting targeted data from the web. - Tom M. Mitchell (KDD, 2001)

Distinguishing Natural Language Processes on the Basis of fMRI-Measured Brain Activation. - Francisco Pereira 001; Marcel Adam Just; Tom M. Mitchell (PKDD, 2001)

Author's response to reviews of Machine Learning. - Tom M. Mitchell (Artif. Intell., 2001)

AAAI 2000 Workshop Reports. - Yves Lespérance; Gerd Wagner 001; 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; et al. (AI Mag., 2001)

Artificial Intelligence and Human Brain Imaging. - Tom M. Mitchell (AI, 2003)

Classifying Instantaneous Cognitive States from fMRI Data. - Tom M. Mitchell; Rebecca A. Hutchinson; Marcel Adam Just; Radu Stefan Niculescu; Francisco Pereira 001; Xuerui Wang (AMIA, 2003)

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

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

AI Matures and Flourishes in North America. - David Mike Hamilton; Tom M. Mitchell; Carol McKenna Hamilton (IEEE Intell. Syst., 2003)

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

Learning to Classify Email into "Speech Acts". - William W. Cohen; Vitor R. Carvalho; Tom M. Mitchell (EMNLP, 2004)

Detecting Significant Multidimensional Spatial Clusters. - Daniel B. Neill; Andrew W. Moore 001; Francisco Pereira 001; Tom M. Mitchell (NIPS, 2004)

Intelligent Workstation Agents and Unstructured Workstation Data. - Tom M. Mitchell (Web Intelligence, 2004)

Learning to Decode Cognitive States from Brain Images. - Tom M. Mitchell; Rebecca A. Hutchinson; Radu Stefan Niculescu; Francisco Pereira 001; Xuerui Wang; Marcel Adam Just; Sharlene D. Newman (Mach. Learn., 2004)

Learning Topic-Based Mixture Models for Factored Classification. - Qiong Chen; Tom M. Mitchell (CIMCA/IAWTIC, 2005)

Machine Learning for Analyzing Human Brain Function. - Tom M. Mitchell (PAKDD, 2005)

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

The 2005 AAAI Classic Paper Awards. - Tom M. Mitchell; Hector J. Levesque (AI Mag., 2005)

Predicting 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 (J. Biomed. Informatics, 2005)

Semi-Supervised Text Classification Using EM. - Kamal Nigam; Andrew McCallum; Tom M. Mitchell (Semi-Supervised Learning, 2006)

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

Hidden process models. - Rebecca A. Hutchinson; Tom M. Mitchell; Indrayana Rustandi (ICML, 2006)

Text clustering with extended user feedback. - Yifen Huang; Tom M. Mitchell (SIGIR, 2006)

Bayesian Network Learning with Parameter Constraints. - Radu Stefan Niculescu; Tom M. Mitchell; R. Bharat Rao (J. Mach. Learn. Res., 2006)

Modeling the fMRI Signal via Hierarchical Clustered Hidden Process Models. - Radu Stefan Niculescu; Tom M. Mitchell; R. Bharat Rao (AMIA, 2007)

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

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

Continuous hidden process model for time series expression experiments. - Yanxin Shi; Michael Klutstein; Itamar Simon; Tom M. Mitchell; Ziv Bar-Joseph (ISMB/ECCB (Supplement of Bioinformatics), 2007)

Learning, Information Extraction and the Web. - Tom M. Mitchell (ECML/PKDD, 2007)

Classification in Very High Dimensional Problems with Handfuls of Examples. - Mark Palatucci; Tom M. Mitchell (PKDD, 2007)

In Honor of Marvin Minsky's Contributions on his 80th Birthday. - Danny Hillis; John McCarthy 001; Tom M. Mitchell; Erik T. Mueller; Doug Riecken; Aaron Sloman; Patrick Henry Winston (AI Mag., 2007)

Inferring pairwise regulatory relationships from multiple time series datasets. - Yanxin Shi; Tom M. Mitchell; Ziv Bar-Joseph (Bioinform., 2007)

Computational Models of Neural Representations in the Human Brain. - Tom M. Mitchell (ALT, 2008)

A Combined Expression-Interaction Model for Inferring the Temporal Activity of Transcription Factors. - Yanxin Shi; Itamar Simon; Tom M. Mitchell; Ziv Bar-Joseph (RECOMB, 2008)

Toward 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)

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

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

Search war: a game for improving web search. - Edith Law; Luis von Ahn; Tom M. Mitchell (KDD Workshop on Human Computation, 2009)

Zero-shot Learning with Semantic Output Codes. - Mark Palatucci; Dean Pomerleau; Geoffrey E. Hinton; Tom M. Mitchell (NIPS, 2009)

Populating the Semantic Web by Macro-reading Internet Text. - Tom M. Mitchell; Justin Betteridge; Andrew Carlson; Estevam R. Hruschka Jr.; Richard C. Wang (ISWC, 2009)

A Combined Expression-Interaction Model for Inferring the Temporal Activity of Transcription Factors. - Yanxin Shi; Michael Klutstein; Itamar Simon; Tom M. Mitchell; Ziv Bar-Joseph (J. Comput. Biol., 2009)

Modeling 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, 2009)

Machine learning classifiers and fMRI: A tutorial overview. - Francisco Pereira 001; Tom M. Mitchell; Matthew M. Botvinick (NeuroImage, 2009)

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

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

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

Which Noun Phrases Denote Which Concepts? - Jayant Krishnamurthy; Tom M. Mitchell (ACL, 2011)

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

Discovering Relations between Noun Categories. - Thahir Mohamed; Estevam R. Hruschka Jr.; Tom M. Mitchell (EMNLP, 2011)

Neural Representations of Word Meanings. - Tom M. Mitchell (INTERSPEECH, 2011)

Quantitative 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, 2011)

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

Acquiring temporal constraints between relations. - Partha Pratim Talukdar; Derry Wijaya; Tom M. Mitchell (CIKM, 2012)

Learning Effective and Interpretable Semantic Models using Non-Negative Sparse Embedding. - Brian Murphy; Partha Pratim Talukdar; Tom M. Mitchell (COLING, 2012)

Never Ending Learning. - Tom M. Mitchell (ECAI, 2012)

Weakly Supervised Training of Semantic Parsers. - Jayant Krishnamurthy; Tom M. Mitchell (EMNLP-CoNLL, 2012)

Selecting Corpus-Semantic Models for Neurolinguistic Decoding. - Brian Murphy; Partha P. Talukdar; Tom M. Mitchell (*SEM@NAACL-HLT, 2012)

Coupled temporal scoping of relational facts. - Partha Pratim Talukdar; Derry Wijaya; Tom M. Mitchell (WSDM, 2012)

Hierarchical Latent Dictionaries for Models of Brain Activation. - Alona Fyshe; Emily B. Fox; David B. Dunson; Tom M. Mitchell (AISTATS, 2012)

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

Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models. - Jayant Krishnamurthy; Tom M. Mitchell (CVSM@ACL, 2013)

PIDGIN: ontology alignment using web text as interlingua. - Derry Wijaya; Partha Pratim Talukdar; Tom M. Mitchell (CIKM, 2013)

Documents and Dependencies: an Exploration of Vector Space Models for Semantic Composition. - Alona Fyshe; Brian Murphy; Partha Pratim Talukdar; Tom M. Mitchell (CoNLL, 2013)

Improving Learning and Inference in a Large Knowledge-Base using Latent Syntactic Cues. - Matt Gardner 001; Partha Pratim Talukdar; Bryan Kisiel; Tom M. Mitchell (EMNLP, 2013)

CMUML System for KBP 2013 Slot Filling. - Bryan Kisiel; Justin Betteridge; Matt Gardner 001; Jayant Krishnamurthy; Ndapa Nakashole; Mehdi Samadi; Partha Pratim Talukdar; Derry Wijaya; Tom M. Mitchell (TAC, 2013)

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

Interpretable Semantic Vectors from a Joint Model of Brain- and Text- Based Meaning. - Alona Fyshe; Partha Pratim Talukdar; Brian Murphy; Tom M. Mitchell (ACL (1), 2014)

Joint Syntactic and Semantic Parsing with Combinatory Categorial Grammar. - Jayant Krishnamurthy; Tom M. Mitchell (ACL (1), 2014)

Language-Aware Truth Assessment of Fact Candidates. - Ndapandula Nakashole; Tom M. Mitchell (ACL (1), 2014)

Incorporating Vector Space Similarity in Random Walk Inference over Knowledge Bases. - Matt Gardner 001; Partha Pratim Talukdar; Jayant Krishnamurthy; Tom M. Mitchell (EMNLP, 2014)

Aligning context-based statistical models of language with brain activity during reading. - Leila Wehbe; Ashish Vaswani; Kevin Knight; Tom M. Mitchell (EMNLP, 2014)

CTPs: Contextual Temporal Profiles for Time Scoping Facts using State Change Detection. - Derry Tanti Wijaya; Ndapandula Nakashole; Tom M. Mitchell (EMNLP, 2014)

Assuming Facts Are Expressed More Than Once. - Justin Betteridge; Alan Ritter; Tom M. Mitchell (FLAIRS, 2014)

Good-enough brain model: challenges, algorithms and discoveries in multi-subject experiments. - Evangelos E. Papalexakis; Alona Fyshe; Nicholas D. Sidiropoulos; Partha Pratim Talukdar; Tom M. Mitchell; Christos Faloutsos (KDD, 2014)

Turbo-SMT: Accelerating Coupled Sparse Matrix-Tensor Factorizations by 200x. - Evangelos E. Papalexakis; Christos Faloutsos; Tom M. Mitchell; Partha Pratim Talukdar; Nicholas D. Sidiropoulos; Brian Murphy (SDM, 2014)

Estimating Accuracy from Unlabeled Data. - Emmanouil Antonios Platanios; Avrim Blum; Tom M. Mitchell (UAI, 2014)

Good-Enough Brain Model: Challenges, Algorithms, and Discoveries in Multisubject Experiments. - Evangelos E. Papalexakis; Alona Fyshe; Nicholas D. Sidiropoulos; Partha Pratim Talukdar; Tom M. Mitchell; Christos Faloutsos (Big Data, 2014)

Efficient Inference and Learning in a Large Knowledge Base: Reasoning with Extracted Information using a Locally Groundable First-Order Probabilistic Logic. - William Yang Wang; Kathryn Mazaitis; Ni Lao; Tom M. Mitchell; William W. Cohen (CoRR, 2014)

Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing. - Jan Kujala; Gustavo P. Sudre; Johanna Vartiainen; Mia Liljeström; Tom M. Mitchell; Riitta Salmelin (NeuroImage, 2014)

Never-Ending Learning. - Tom M. Mitchell; William W. Cohen; Estevam R. Hruschka Jr.; Partha Pratim Talukdar; Justin Betteridge; Andrew Carlson; Bhavana Dalvi Mishra; Matthew Gardner 001; Bryan Kisiel; Jayant Krishnamurthy; Ni Lao; Kathryn Mazaitis; et al. (AAAI, 2015)

Combining Vector Space Embeddings with Symbolic Logical Inference over Open-Domain Text. - Matt Gardner 001; Partha P. Talukdar; Tom Michael Mitchell (AAAI Spring Symposia, 2015)

A Knowledge-Intensive Model for Prepositional Phrase Attachment. - Ndapandula Nakashole; Tom M. Mitchell (ACL (1), 2015)

Sense discovery via co-clustering on images and text. - Xinlei Chen; Alan Ritter; Abhinav Gupta 001; Tom M. Mitchell (CVPR, 2015)

Efficient and Expressive Knowledge Base Completion Using Subgraph Feature Extraction. - Matt Gardner 001; Tom M. Mitchell (EMNLP, 2015)

Translation Invariant Word Embeddings. - Kejun Huang; Matt Gardner 001; Evangelos E. Papalexakis; Christos Faloutsos; Nikos D. Sidiropoulos; Tom M. Mitchell; Partha Pratim Talukdar; Xiao Fu 001 (EMNLP, 2015)

"A Spousal Relation Begins with a Deletion of engage and Ends with an Addition of divorce": Learning State Changing Verbs from Wikipedia Revision History. - Derry Tanti Wijaya; Ndapandula Nakashole; Tom M. Mitchell (EMNLP, 2015)

AskWorld: Budget-Sensitive Query Evaluation for Knowledge-on-Demand. - Mehdi Samadi; Partha Pratim Talukdar; Manuela M. Veloso; Tom M. Mitchell (IJCAI, 2015)

A Compositional and Interpretable Semantic Space. - Alona Fyshe; Leila Wehbe; Partha Pratim Talukdar; Brian Murphy; Tom M. Mitchell (HLT-NAACL, 2015)

Principled Neuro-Functional Connectivity Discovery. - Kejun Huang; Nicholas D. Sidiropoulos; Evangelos E. Papalexakis; Christos Faloutsos; Partha Pratim Talukdar; Tom M. Mitchell (SDM, 2015)

CMUML System for KBP 2015 Cold Start Slot Filling. - Bryan Kisiel; Bill McDowell; Matt Gardner 001; Ndapandula Nakashole; Emmanouil A. Platanios; Abulhair Saparov; Shashank Srivastava; Derry Wijaya; Tom M. Mitchell (TAC, 2015)

Weakly Supervised Extraction of Computer Security Events from Twitter. - Alan Ritter; Evan Wright; William Casey; Tom M. Mitchell (WWW, 2015)

Learning a Compositional Semantics for Freebase with an Open Predicate Vocabulary. - Jayant Krishnamurthy; Tom M. Mitchell (Trans. Assoc. Comput. Linguistics, 2015)

Instructable Intelligent Personal Agent. - Amos Azaria; Jayant Krishnamurthy; Tom M. Mitchell (AAAI, 2016)

Inferring Interpersonal Relations in Narrative Summaries. - Shashank Srivastava; Snigdha Chaturvedi; Tom M. Mitchell (AAAI, 2016)

Efficient and Distributed Algorithms for Large-Scale Generalized Canonical Correlations Analysis. - Xiao Fu 001; Kejun Huang; Evangelos E. Papalexakis; Hyun Ah Song; Partha Pratim Talukdar; Nicholas D. Sidiropoulos; Christos Faloutsos; Tom M. Mitchell (ICDM, 2016)

Estimating Accuracy from Unlabeled Data: A Bayesian Approach. - Emmanouil Antonios Platanios; Avinava Dubey; Tom M. Mitchell (ICML, 2016)

Mapping Verbs in Different Languages to Knowledge Base Relations using Web Text as Interlingua. - Derry Tanti Wijaya; Tom M. Mitchell (HLT-NAACL, 2016)

Joint Extraction of Events and Entities within a Document Context. - Bishan Yang; Tom M. Mitchell (HLT-NAACL, 2016)

CMUML Micro-Reader System for KBP 2016 Cold Start Slot Filling, Event Nugget Detection, and Event Argument Linking. - Bishan Yang; Ndapandula Nakashole; Bryan Kisiel; Emmanouil A. Platanios; Abulhair Saparov; Shashank Srivastava; Derry Wijaya; Tom M. Mitchell (TAC, 2016)

Machine Reading with Background Knowledge. - Ndapandula Nakashole; Tom M. Mitchell (CoRR, 2016)

A Probabilistic Generative Grammar for Semantic Parsing. - Abulhair Saparov; Tom M. Mitchell (CoRR, 2016)

Turbo-SMT: Parallel coupled sparse matrix-Tensor factorizations and applications. - Evangelos E. Papalexakis; Tom M. Mitchell; Nicholas D. Sidiropoulos; Christos Faloutsos; Partha Pratim Talukdar; Brian Murphy (Stat. Anal. Data Min., 2016)

Leveraging Knowledge Bases in LSTMs for Improving Machine Reading. - Bishan Yang; Tom M. Mitchell (ACL (1), 2017)

A Probabilistic Generative Grammar for Semantic Parsing. - Abulhair Saparov; Vijay A. Saraswat; Tom M. Mitchell (CoNLL, 2017)

Joint Concept Learning and Semantic Parsing from Natural Language Explanations. - Shashank Srivastava; Igor Labutov; Tom M. Mitchell (EMNLP, 2017)

A Joint Sequential and Relational Model for Frame-Semantic Parsing. - Bishan Yang; Tom M. Mitchell (EMNLP, 2017)

Parsing Natural Language Conversations using Contextual Cues. - Shashank Srivastava; Amos Azaria; Tom M. Mitchell (IJCAI, 2017)

Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach. - Emmanouil A. Platanios; Hoifung Poon; Tom M. Mitchell; Eric Horvitz (NIPS, 2017)

BrainZoom: High Resolution Reconstruction from Multi-modal Brain Signals. - Xiao Fu 001; Kejun Huang; Otilia Stretcu; Hyun Ah Song; Evangelos E. Papalexakis; Partha P. Talukdar; Tom M. Mitchell; Nicholas D. Sidiropoulos; Christos Faloutsos; Barnabás Póczos (SDM, 2017)

Merging knowledge bases in different languages. - Jerónimo Hernández-González; Estevam R. Hruschka Jr.; Tom M. Mitchell (TextGraphs@ACL, 2017)

An entity graph based Recommender System. - Sneha Chaudhari; Amos Azaria; Tom M. Mitchell (AI Commun., 2017)

Zero-shot Learning of Classifiers from Natural Language Quantification. - Shashank Srivastava; Igor Labutov; Tom M. Mitchell (ACL (1), 2018)

LIA: A Natural Language Programmable Personal Assistant. - Igor Labutov; Shashank Srivastava; Tom M. Mitchell (EMNLP (Demonstration), 2018)

Learning to Learn Semantic Parsers from Natural Language Supervision. - Igor Labutov; Bishan Yang; Tom M. Mitchell (EMNLP, 2018)

Contextual Parameter Generation for Universal Neural Machine Translation. - Emmanouil Antonios Platanios; Mrinmaya Sachan; Graham Neubig; Tom M. Mitchell (EMNLP, 2018)

Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems. - Mrinmaya Sachan; Kumar Avinava Dubey; Tom M. Mitchell; Dan Roth 001; Eric P. Xing (NeurIPS, 2018)

APPINITE: A Multi-Modal Interface for Specifying Data Descriptions in Programming by Demonstration Using Natural Language Instructions. - Toby Jia-Jun Li; Igor Labutov; Xiaohan Nancy Li; Xiaoyi Zhang 006; Wenze Shi; Wanling Ding; Tom M. Mitchell; Brad A. Myers (VL/HCC, 2018)

Never-ending learning. - Tom M. Mitchell; William W. Cohen; Estevam R. Hruschka Jr.; Partha P. Talukdar; Bo Yang 011; Justin Betteridge; Andrew Carlson; Bhavana Dalvi Mishra; Matt Gardner 001; Bryan Kisiel; Jayant Krishnamurthy; Ni Lao; et al. (Commun. ACM, 2018)

Discourse in Multimedia: A Case Study in Information Extraction. - Mrinmaya Sachan; Kumar Avinava Dubey; Eduard H. Hovy; Tom M. Mitchell; Dan Roth 001; Eric P. Xing (CoRR, 2018)

Teaching Agents When They Fail: End User Development in Goal-Oriented Conversational Agents. - Toby Jia-Jun Li; Igor Labutov; Brad A. Myers; Amos Azaria; Alexander I. Rudnicky; Tom M. Mitchell (Studies in Conversational UX Design, 2018)

Relating Simple Sentence Representations in Deep Neural Networks and the Brain. - Sharmistha Jat; Hao Tang; Partha P. Talukdar; Tom M. Mitchell (ACL (1), 2019)

Look-up and Adapt: A One-shot Semantic Parser. - Zhichu Lu; Forough Arabshahi; Igor Labutov; Tom M. Mitchell (EMNLP/IJCNLP (1), 2019)

Learning to Ask for Conversational Machine Learning. - Shashank Srivastava; Igor Labutov; Tom M. Mitchell (EMNLP/IJCNLP (1), 2019)

Competence-based Curriculum Learning for Neural Machine Translation. - Emmanouil Antonios Platanios; Otilia Stretcu; Graham Neubig; Barnabás Póczos; Tom M. Mitchell (NAACL-HLT (1), 2019)

Understanding language-elicited EEG data by predicting it from a fine-tuned language model. - Dan Schwartz; Tom M. Mitchell (NAACL-HLT (1), 2019)

Learning Data Manipulation for Augmentation and Weighting. - Zhiting Hu; Bowen Tan; Ruslan Salakhutdinov; Tom M. Mitchell; Eric P. Xing (NeurIPS, 2019)

Game Design for Eliciting Distinguishable Behavior. - Fan Yang 058; Liu Leqi; Yifan Wu; Zachary Chase Lipton; Pradeep Ravikumar; Tom M. Mitchell; William W. Cohen (NeurIPS, 2019)

PUMICE: A Multi-Modal Agent that Learns Concepts and Conditionals from Natural Language and Demonstrations. - Toby Jia-Jun Li; Marissa Radensky; Justin Jia; Kirielle Singarajah; Tom M. Mitchell; Brad A. Myers (UIST, 2019)

Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks. - Mrinmaya Sachan; Avinava Dubey; Eduard H. Hovy; Tom M. Mitchell; Dan Roth 001; Eric P. Xing (Comput. Linguistics, 2019)

Efficient and Distributed Generalized Canonical Correlation Analysis for Big Multiview Data. - Xiao Fu 001; Kejun Huang; Evangelos E. Papalexakis; Hyun Ah Song; Partha P. Talukdar; Nicholas D. Sidiropoulos; Christos Faloutsos; Tom M. Mitchell (IEEE Trans. Knowl. Data Eng., 2019)

Contextual Parameter Generation for Knowledge Graph Link Prediction. - George Stoica; Otilia Stretcu; Emmanouil Antonios Platanios; Tom M. Mitchell; Barnabás Póczos (AAAI, 2020)

Interactive Task Learning from GUI-Grounded Natural Language Instructions and Demonstrations. - Toby Jia-Jun Li; Tom M. Mitchell; Brad A. Myers (ACL (demo), 2020)

Jelly Bean World: A Testbed for Never-Ending Learning. - Emmanouil Antonios Platanios; Abulhair Saparov; Tom M. Mitchell (ICLR, 2020)

Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction. - Mariya Toneva; Otilia Stretcu; Barnabás Póczos; Leila Wehbe; Tom M. Mitchell (NeurIPS, 2020)

Multi-Modal Repairs of Conversational Breakdowns in Task-Oriented Dialogs. - Toby Jia-Jun Li; Jingya Chen; Haijun Xia; Tom M. Mitchell; Brad A. Myers (UIST, 2020)

An agent for learning new natural language commands. - Amos Azaria; Shashank Srivastava; Jayant Krishnamurthy; Igor Labutov; Tom M. Mitchell (Auton. Agents Multi Agent Syst., 2020)

Towards Effective Human-AI Collaboration in GUI-Based Interactive Task Learning Agents. - Toby Jia-Jun Li; Jingya Chen; Tom M. Mitchell; Brad A. Myers (CoRR, 2020)

Learning from Imperfect Annotations. - Emmanouil Antonios Platanios; Maruan Al-Shedivat; Eric P. Xing; Tom M. Mitchell (CoRR, 2020)

From Data to Knowledge to Action: A Global Enabler for the 21st Century. - Eric Horvitz; Tom M. Mitchell (CoRR, 2020)

Discovering Bilingual Lexicons in Polyglot Word Embeddings. - Ashiqur R. KhudaBukhsh; Shriphani Palakodety; Tom M. Mitchell (CoRR, 2020)

Conversational Neuro-Symbolic Commonsense Reasoning. - Forough Arabshahi; Jennifer Lee; Mikayla Gawarecki; Kathryn Mazaitis; Amos Azaria; Tom M. Mitchell (AAAI, 2021)

We Don't Speak the Same Language: Interpreting Polarization through Machine Translation. - Ashiqur R. KhudaBukhsh; Rupak Sarkar; Mark S. Kamlet; Tom M. Mitchell (AAAI, 2021)

Screen2Vec: Semantic Embedding of GUI Screens and GUI Components. - Toby Jia-Jun Li; Lindsay Popowski; Tom M. Mitchell; Brad A. Myers (CHI, 2021)

Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules. - Forough Arabshahi; Jennifer Lee; Antoine Bosselut; Yejin Choi 001; Tom M. Mitchell (EMNLP (1), 2021)

WIT: Workshop on deriving Insights from user-generated Text. - Estevam Hruschka; Tom M. Mitchell; Marko Grobelnik; Behzad Golshan (KDD, 2021)

Can We Replace Programming Languages by Natural Instruction? - Tom M. Mitchell (WI/IAT, 2021)

Gender Bias, Social Bias and Representation: 70 Years of B$^H$ollywood. - Kunal Khadilkar; Ashiqur R. KhudaBukhsh; Tom M. Mitchell (CoRR, 2021)

A Generative Symbolic Model for More General Natural Language Understanding and Reasoning. - Abulhair Saparov; Tom M. Mitchell (CoRR, 2021)

Coarse-to-Fine Curriculum Learning. - Otilia Stretcu; Emmanouil Antonios Platanios; Tom M. Mitchell; Barnabás Póczos (CoRR, 2021)

Assessing the Knowledge State of Online Students - New Data, New Approaches, Improved Accuracy. - Robin Schmucker; Jingbo Wang; Shijia Hu; Tom M. Mitchell (CoRR, 2021)

Transferable Student Performance Modeling for Intelligent Tutoring Systems. - Robin Schmucker; Tom M. Mitchell (ICCE, 2022)

Harnessing Unsupervised Word Translation to Address Resource Inequality for Peace and Health. - Ashiqur R. KhudaBukhsh; Shriphani Palakodety; Tom M. Mitchell (SocInfo, 2022)

Fringe News Networks: Dynamics of US News Viewership following the 2020 Presidential Election. - Ashiqur R. KhudaBukhsh; Rupak Sarkar; Mark S. Kamlet; Tom M. Mitchell (WebSci, 2022)

Combining computational controls with natural text reveals aspects of meaning composition. - Mariya Toneva; Tom M. Mitchell; Leila Wehbe (Nat. Comput. Sci., 2022)

Gender bias, social bias, and representation: 70 years of BHollywood. - Kunal Khadilkar; Ashiqur R. KhudaBukhsh; Tom M. Mitchell (Patterns, 2022)

Gender bias, social bias, and representation in Bollywood and Hollywood. - Kunal Khadilkar; Ashiqur R. KhudaBukhsh; Tom M. Mitchell (Patterns, 2022)

Towards General Natural Language Understanding with Probabilistic Worldbuilding. - Abulhair Saparov; Tom M. Mitchell (Trans. Assoc. Comput. Linguistics, 2022)

Learning to Give Useful Hints: Assistance Action Evaluation and Policy Improvements. - Robin Schmucker; Nimish Pachapurkar; Bala Shanmugam; Miral Shah; Tom M. Mitchell (EC-TEL, 2023)

The Internal State of an LLM Knows When It's Lying. - Amos Azaria; Tom M. Mitchell (EMNLP (Findings), 2023)

Zero-shot Triplet Extraction by Template Infilling. - Bosung Kim; Hayate Iso; Nikita Bhutani; Estevam Hruschka; Ndapa Nakashole; Tom M. Mitchell (IJCNLP (1), 2023)

The Roles of Symbols in Neural-based AI: They are Not What You Think! - Daniel L. Silver; Tom M. Mitchell (NeSy, 2023)

Read and Reap the Rewards: Learning to Play Atari with the Help of Instruction Manuals. - Yue Wu 001; Yewen Fan; Paul Pu Liang; Amos Azaria; Yuanzhi Li; Tom M. Mitchell (NeurIPS, 2023)

SPRING: Studying Papers and Reasoning to play Games. - Yue Wu 001; So Yeon Min; Shrimai Prabhumoye; Yonatan Bisk; Russ Salakhutdinov; Amos Azaria; Tom M. Mitchell; Yuanzhi Li (NeurIPS, 2023)

The Internal State of an LLM Knows When its Lying. - Amos Azaria; Tom M. Mitchell (CoRR, 2023)

Plan, Eliminate, and Track - Language Models are Good Teachers for Embodied Agents. - Yue Wu 001; So Yeon Min; Yonatan Bisk; Ruslan Salakhutdinov; Amos Azaria; Yuanzhi Li; Tom M. Mitchell; Shrimai Prabhumoye (CoRR, 2023)

SPRING: GPT-4 Out-performs RL Algorithms by Studying Papers and Reasoning. - Yue Wu 001; Shrimai Prabhumoye; So Yeon Min; Yonatan Bisk; Ruslan Salakhutdinov; Amos Azaria; Tom M. Mitchell; Yuanzhi Li (CoRR, 2023)

Ruffle&Riley: Towards the Automated Induction of Conversational Tutoring Systems. - Robin Schmucker; Meng Xia 002; Amos Azaria; Tom M. Mitchell (CoRR, 2023)

The Roles of Symbols in Neural-Based AI: They Are Not What You Think! - Daniel L. Silver; Tom M. Mitchell (Compendium of Neurosymbolic Artificial Intelligence, 2023)

Ruffle &Riley: Insights from Designing and Evaluating a Large Language Model-Based Conversational Tutoring System. - Robin Schmucker; Meng Xia 002; Amos Azaria; Tom M. Mitchell (AIED (1), 2024)

SmartPlay : A Benchmark for LLMs as Intelligent Agents. - Yue Wu 001; Xuan Tang; Tom M. Mitchell; Yuanzhi Li (ICLR, 2024)

Automated Generation and Tagging of Knowledge Components from Multiple-Choice Questions. - Steven Moore; Robin Schmucker; Tom M. Mitchell; John C. Stamper (L@S, 2024)

Ruffle&Riley: From Lesson Text to Conversational Tutoring. - Robin Schmucker; Meng Xia 002; Amos Azaria; Tom M. Mitchell (L@S, 2024)

Reasoning Capacity in Multi-Agent Systems: Limitations, Challenges and Human-Centered Solutions. - Pouya Pezeshkpour; Eser Kandogan; Nikita Bhutani; Sajjadur Rahman; Tom M. Mitchell; Estevam Hruschka (CoRR, 2024)

AgentKit: Flow Engineering with Graphs, not Coding. - Yue Wu 001; Yewen Fan; So Yeon Min; Shrimai Prabhumoye; Stephen McAleer; Yonatan Bisk; Ruslan Salakhutdinov; Yuanzhi Li; Tom M. Mitchell (CoRR, 2024)

Heterogeneous Treatment Effects of Learning Analytics Dashboards: Do All Learners Benefit Equally? - Aylin Ozturk; Robin Schmucker; Tom M. Mitchell; Alper Tolga Kumtepe (EDM, 2025)

AI Mentors for Student Projects: Spotting Early Issues in Computer Science Proposals. - Gati Aher; Robin Schmucker; Tom M. Mitchell; Zachary C. Lipton (CoRR, 2025)

Learning to Optimize Feedback for One Million Students: Insights from Multi-Armed and Contextual Bandits in Large-Scale Online Tutoring. - Robin Schmucker; Nimish Pachapurkar; Bala Shanmugam; Miral Shah; Tom M. Mitchell (CoRR, 2025)