| 2016 | ILP | Learning Relational Dependency Networks for Relation Extraction. | Ameet Soni, Dileep Viswanathan, Jude W. Shavlik, Sriraam Natarajan |
| 2015 | FlAIRS | Anomaly Detection in Text: The Value of Domain Knowledge. | Raksha Kumaraswamy, Anurag Wazalwar, Tushar Khot, Jude W. Shavlik, Sriraam Natarajan |
| 2014 | AAAI | Relational One-Class Classification: A Non-Parametric Approach. | Tushar Khot, Sriraam Natarajan, Jude W. Shavlik |
| 2014 | AAAI | Classification from One Class of Examples for Relational Domains. | Tushar Khot, Sriraam Natarajan, Jude W. Shavlik |
| 2014 | ILP | Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge. | Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher R, Jude W. Shavlik |
| 2014 | SIGIR | Detecting Semantic Uncertainty by Learning Hedge Cues in Sentences Using an HMM. | Xiujun Li, Wei Gao, Jude W. Shavlik |
| 2014 | SIGMOD | Corleone: hands-off crowdsourcing for entity matching. | Chaitanya Gokhale, Sanjib Das, AnHai Doan, Jeffrey F. Naughton, Narasimhan Rampalli, Jude W. Shavlik, Xiaojin Zhu |
| 2013 | AAAI | Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text. | Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher R, Jude W. Shavlik |
| 2013 | AMIA | Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms. | Jie Liu, David Page, Houssam Nassif, Jude W. Shavlik, Peggy L. Peissig, Catherine A. McCarty, Adedayo A. Onitilo, Elizabeth S. Burnside |
| 2013 | HealthCom | Using machine learning to identify benign cases with non-definitive biopsy. | Finn Kuusisto, Ins de Castro Dutra, Houssam Nassif, Yirong Wu, Molly E. Klein, Heather B. Neuman, Jude W. Shavlik, Elizabeth S. Burnside |
| 2013 | ICDM | Guiding Autonomous Agents to Better Behaviors through Human Advice. | Gautam Kunapuli, Phillip Odom, Jude W. Shavlik, Sriraam Natarajan |
| 2013 | ILP | Uplift Modeling with ROC: An SRL Case Study. | Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, Jude W. Shavlik |
| 2012 | ACL | Big Data versus the Crowd: Looking for Relationships in All the Right Places. | Ce Zhang, Feng Niu, Christopher R, Jude W. Shavlik |
| 2012 | ICDM | Scaling Inference for Markov Logic via Dual Decomposition. | Feng Niu, Ce Zhang, Christopher R, Jude W. Shavlik |
| 2012 | NeSy | Twenty-Five Years of Combining Symbolic and Numeric Learning. | Jude W. Shavlik |
| 2011 | ICDM | Learning Markov Logic Networks via Functional Gradient Boosting. | Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik |
| 2011 | IJCAI | Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach. | Sriraam Natarajan, Saket Joshi, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik |
| 2010 | AAAI | Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. | Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik |
| 2010 | ICMLA | Multi-Agent Inverse Reinforcement Learning. | Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik |
| 2010 | ILP | Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge. | Trevor Walker, Ciaran O'Reilly, Gautam Kunapuli, Sriraam Natarajan, Richard Maclin, David Page, Jude W. Shavlik |
| 2009 | ICDM | Information Extraction for Clinical Data Mining: A Mammography Case Study. | Houssam Nassif, Ryan W. Woods, Elizabeth S. Burnside, Mehmet Ayvaci, Jude W. Shavlik, David Page |
| 2009 | ICMLA | Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule. | Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapuli, Jude W. Shavlik |
| 2009 | IJCAI | Speeding Up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network. | Jude W. Shavlik, Sriraam Natarajan |
| 2009 | ILP | Boosting First-Order Clauses for Large, Skewed Data Sets. | Louis Oliphant, Elizabeth S. Burnside, Jude W. Shavlik |
| 2009 | ILP | Policy Transfer via Markov Logic Networks. | Lisa Torrey, Jude W. Shavlik |
| 2007 | AAAI | Refining Rules Incorporated into Knowledge-Based Support Vector Learners Via Successive Linear Programming. | Richard Maclin, Edward W. Wild, Jude W. Shavlik, Lisa Torrey, Trevor Walker |
| 2007 | ILP | Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates. | Mark H. Goadrich, Jude W. Shavlik |
| 2007 | ILP | Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming. | Louis Oliphant, Jude W. Shavlik |
| 2007 | ILP | Relational Macros for Transfer in Reinforcement Learning. | Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin |
| 2007 | ILP | Building Relational World Models for Reinforcement Learning. | Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richard Maclin |
| 2006 | AAAI | A Simple and Effective Method for Incorporating Advice into Kernel Methods. | Richard Maclin, Jude W. Shavlik, Trevor Walker, Lisa Torrey |
| 2006 | ICDM | Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition. | Frank DiMaio, Jude W. Shavlik |
| 2006 | ISMB | A probabilistic approach to protein backbone tracing in electron density maps. | Frank DiMaio, Jude W. Shavlik, George N. Phillips |
| 2006 | VLDB | Bellwether Analysis: Predicting Global Aggregates from Local Regions. | Bee-Chung Chen, Raghu Ramakrishnan, Jude W. Shavlik, Pradeep Tamma |
| 2005 | AAAI | Giving Advice about Preferred Actions to Reinforcement Learners Via Knowledge-Based Kernel Regression. | Richard Maclin, Jude W. Shavlik, Lisa Torrey, Trevor Walker, Edward W. Wild |
| 2005 | IJCAI | View Learning for Statistical Relational Learning: With an Application to Mammography. | Jesse Davis, Elizabeth S. Burnside, Ins de Castro Dutra, David Page, Raghu Ramakrishnan, Vtor Santos Costa, Jude W. Shavlik |
| 2005 | ILP | A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment. | Hctor Corrada Bravo, David Page, Raghu Ramakrishnan, Jude W. Shavlik, Vtor Santos Costa |
| 2004 | ILP | Learning an Approximation to Inductive Logic Programming Clause Evaluation. | Frank DiMaio, Jude W. Shavlik |
| 2004 | ILP | Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction. | Mark H. Goadrich, Louis Oliphant, Jude W. Shavlik |
| 2004 | ILP | Scaling Up ILP: Experiences with Extracting Relations from Biomedical Text. | Jude W. Shavlik |
| 2004 | KDD | Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage. | Jude W. Shavlik, Mark Shavlik |
| 2003 | COLT | Knowledge-Based Nonlinear Kernel Classifiers. | Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik |
| 2003 | EuroPar | Toward Automatic Management of Embarrassingly Parallel Applications. | Ins de Castro Dutra, David Page, Vtor Santos Costa, Jude W. Shavlik, Michael Waddell |
| 2003 | ILP | Applying Theory Revision to the Design of Distributed Databases. | Fernanda Arajo Baio, Marta Mattoso, Jude W. Shavlik, Gerson Zaverucha |
| 2002 | ILP | An Empirical Evaluation of Bagging in Inductive Logic Programming. | Ins de Castro Dutra, David Page, Vtor Santos Costa, Jude W. Shavlik |
| 2002 | ISMB | Evaluating machine learning approaches for aiding probe selection for gene-expression arrays. | J. B. Tobler, Michael Molla, Emile F. Nuwaysir, R. D. Green, Jude W. Shavlik |
| 2001 | ICML | A Theory-Refinement Approach to Information Extraction. | Tina Eliassi-Rad, Jude W. Shavlik |
| 2000 | ICML | Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes. | Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner |
| 2000 | ISMB | A Probabilistic Learning Approach to Whole-Genome Operon Prediction. | Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner |
| 2000 | IUI | Learning users' interests by unobtrusively observing their normal behavior. | Jeremy Goecks, Jude W. Shavlik |
| 1999 | IUI | Bridging Science and Applications (Panel). | Jude W. Shavlik, Lawrence Birnbaum, William R. Swartout, Eric Horvitz, Barbara Hayes-Roth |
| 1999 | IUI | An Instructable, Adaptive Interface for Discovering and Monitoring Information on the World-Wide Web. | Jude W. Shavlik, Susan Calcari, Tina Eliassi-Rad, Jack Solock |
| 1997 | ISMB | Increasing Consensus Accuracy in DNA Fragment Assemblies by Incorporating Fluorescent Trace Representations. | Carolyn F. Allex, Schuyler F. Baldwin, Jude W. Shavlik, Frederick R. Blattner |
| 1996 | ISMB | Improving the Quality of Automatic DNA Sequence Assembly Using Fluorescent Trace-Data Classifications. | Carolyn F. Allex, Schuyler F. Baldwin, Jude W. Shavlik, Frederick R. Blattner |
| 1996 | KDD | Growing Simpler Decision Trees to Facilitate Knowledge Discovery. | Kevin J. Cherkauer, Jude W. Shavlik |
| 1995 | IJCAI | Combining the Predictions of Multiple Classifiers: Using Competitive Learning to Initialize Neural Networks. | Richard Maclin, Jude W. Shavlik |
| 1994 | AAAI | Incorporating Advice into Agents that Learn from Reinforcements. | Richard Maclin, Jude W. Shavlik |
| 1994 | ICML | Using Sampling and Queries to Extract Rules from Trained Neural Networks. | Mark W. Craven, Jude W. Shavlik |
| 1994 | ICML | Using Genetic Search to Refine Knowledge-based Neural Networks. | David W. Opitz, Jude W. Shavlik |
| 1993 | ICML | Learning Symbolic Rules Using Artificial Neural Networks. | Mark W. Craven, Jude W. Shavlik |
| 1993 | IJCAI | Learning to Represent Codons: A Challenge Problem for Constructive Induction. | Mark W. Craven, Jude W. Shavlik |
| 1993 | IJCAI | Heuristically Expanding Knowledge-Based Neural Networks. | David W. Opitz, Jude W. Shavlik |
| 1993 | ISMB | Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools. | Kevin J. Cherkauer, Jude W. Shavlik |
| 1992 | AAAI | Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein Folding. | Richard Maclin, Jude W. Shavlik |
| 1992 | AAAI | Using Symbolic Learning to Improve Knowledge-Based Neural Networks. | Geoffrey G. Towell, Jude W. Shavlik |
| 1991 | ICML | Refining Domain Theories Expressed as Finite-State Automata. | Richard Maclin, Jude W. Shavlik |
| 1991 | ICML | Constructive Induction in Knowledge-Based Neural Networks. | Geoffrey G. Towell, Mark W. Craven, Jude W. Shavlik |
| 1990 | AAAI | Refinement ofApproximate Domain Theories by Knowledge-Based Neural Networks. | Geoffrey G. Towell, Jude W. Shavlik, Michiel O. Noordewier |
| 1989 | ICML | Processing Issues in Comparisons of Symbolic and Connectionist Learning Systems. | Douglas H. Fisher, Kathleen B. McKusick, Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. Towell |
| 1989 | ICML | Enriching Vocabularies by Generalizing Explanation Structures. | Richard Maclin, Jude W. Shavlik |
| 1989 | ICML | An Empirical Analysis of EBL Approaches for Learning Plan Schemata. | Jude W. Shavlik |
| 1989 | ICML | Combining Explanation-Based Learning and Artificial Neural Networks. | Jude W. Shavlik, Geoffrey G. Towell |
| 1989 | IJCAI | An Experimental Comparison of Symbolic and Connectionist Learning Algorithms. | Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. Towell, Alan Gove |
| 1989 | IJCAI | Acquiring Recursive Concepts with Explanation-Based Learning. | Jude W. Shavlik |
| 1987 | AAAI | BAGGER: An EBL System that Extends and Generalizes Explanations. | Jude W. Shavlik, Gerald DeJong |
| 1987 | IJCAI | An Explanation-based Approach to Generalizing Number. | Jude W. Shavlik, Gerald DeJong |
| 1986 | ISSAC | Computer understanding and generalization of symbolic mathematical calculations: a case study in physics problem solving. | Jude W. Shavlik, Gerald DeJong |
| 1985 | IJCAI | Learning about Momentum Conservation. | Jude W. Shavlik |