Shavlik, Jude W.

62 publications

MLJ 2015 Gradient-Based Boosting for Statistical Relational Learning: The Markov Logic Network and Missing Data Cases Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik

AAAI 2014 Relational One-Class Classification: A Non-Parametric Approach Tushar Khot, Sriraam Natarajan, Jude W. Shavlik

ECML-PKDD 2014 Support Vector Machines for Differential Prediction Finn Kuusisto, Vítor Santos Costa, Houssam Nassif, Elizabeth S. Burnside, David Page, Jude W. Shavlik

ECML-PKDD 2013 Score as You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, David Page, Jude W. Shavlik, Vítor Santos Costa

MLJ 2012 Gradient-Based Boosting for Statistical Relational Learning: The Relational Dependency Network Case Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann, Jude W. Shavlik

ECML-PKDD 2012 Mirror Descent for Metric Learning: A Unified Approach Gautam Kunapuli, Jude W. Shavlik

NeurIPS 2011 Advice Refinement in Knowledge-Based SVMs Gautam Kunapuli, Richard Maclin, Jude W. Shavlik

IJCAI 2011 Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach Sriraam Natarajan, Saket Joshi, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik

ECML-PKDD 2010 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

ECML-PKDD 2010 Online Knowledge-Based Support Vector Machines Gautam Kunapuli, Kristin P. Bennett, Amina Shabbeer, Richard Maclin, Jude W. Shavlik

IJCAI 2009 Speeding up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network Jude W. Shavlik, Sriraam Natarajan

MLJ 2008 Guest Editors' Introduction: Special Issue on Inductive Logic Programming (ILP-2007) Hendrik Blockeel, Jude W. Shavlik, Prasad Tadepalli

AAAI 2007 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

AAAI 2006 A Simple and Effective Method for Incorporating Advice into Kernel Methods Richard Maclin, Jude W. Shavlik, Trevor Walker, Lisa Torrey

MLJ 2006 Gleaner: Creating Ensembles of First-Order Clauses to Improve Recall-Precision Curves Mark H. Goadrich, Louis Oliphant, Jude W. Shavlik

ECML-PKDD 2006 Skill Acquisition via Transfer Learning and Advice Taking Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin

AAAI 2005 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

ECML-PKDD 2005 Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richard Maclin

IJCAI 2005 View Learning for Statistical Relational Learning: With an Application to Mammography Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Raghu Ramakrishnan, Vítor Santos Costa, Jude W. Shavlik

JMLR 2004 Knowledge-Based Kernel Approximation Olvi L. Mangasarian, Jude W. Shavlik, Edward W. Wild

NeurIPS 2004 Pictorial Structures for Molecular Modeling: Interpreting Density Maps Frank Dimaio, George Phillips, Jude W. Shavlik

COLT 2003 Knowledge-Based Nonlinear Kernel Classifiers Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik

NeurIPS 2002 Knowledge-Based Support Vector Machine Classifiers Glenn M. Fung, Olvi L. Mangasarian, Jude W. Shavlik

ICML 2001 A Theory-Refinement Approach to Information Extraction Tina Eliassi-Rad, Jude W. Shavlik

ICML 2000 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

ICML 1998 Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), Madison, Wisconsin, USA, July 24-27, 1998 Jude W. Shavlik

JAIR 1997 Connectionist Theory Refinement: Genetically Searching the Space of Network Topologies David W. Opitz, Jude W. Shavlik

MLJ 1996 Creating Advice-Taking Reinforcement Learners Richard Maclin, Jude W. Shavlik

IJCAI 1995 Combining the Predictions of Multiple Classifiers: Using Competitive Learning to Initialize Neural Networks Richard Maclin, Jude W. Shavlik

NeurIPS 1995 Extracting Tree-Structured Representations of Trained Networks Mark Craven, Jude W. Shavlik

NeurIPS 1995 Generating Accurate and Diverse Members of a Neural-Network Ensemble David W. Opitz, Jude W. Shavlik

MLJ 1995 Introduction Jude W. Shavlik, Lawrence Hunter, David B. Searls

NeurIPS 1995 Rapid Quality Estimation of Neural Network Input Representations Kevin J. Cherkauer, Jude W. Shavlik

MLJ 1994 Combining Symbolic and Neural Learning Jude W. Shavlik

AAAI 1994 Incorporating Advice into Agents That Learn from Reinforcements Richard Maclin, Jude W. Shavlik

ICML 1994 Using Genetic Search to Refine Knowledge-Based Neural Networks David W. Opitz, Jude W. Shavlik

ICML 1994 Using Sampling and Queries to Extract Rules from Trained Neural Networks Mark W. Craven, Jude W. Shavlik

MLJ 1993 Extracting Refined Rules from Knowledge-Based Neural Networks Geoffrey G. Towell, Jude W. Shavlik

IJCAI 1993 Heuristically Expanding Knowledge-Based Neural Networks David W. Opitz, Jude W. Shavlik

ICML 1993 Learning Symbolic Rules Using Artificial Neural Networks Mark W. Craven, Jude W. Shavlik

IJCAI 1993 Learning to Represent Codons: A Challenge Problem for Constructive Induction Mark W. Craven, Jude W. Shavlik

MLJ 1993 Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein Folding Richard Maclin, Jude W. Shavlik

NeCo 1992 Refining PID Controllers Using Neural Networks Gary M. Scott, Jude W. Shavlik, W. Harmon Ray

AAAI 1992 Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein Folding Richard Maclin, Jude W. Shavlik

AAAI 1992 Using Symbolic Learning to Improve Knowledge-Based Neural Networks Geoffrey G. Towell, Jude W. Shavlik

ICML 1991 Constructive Induction in Knowledge-Based Neural Networks Geoffrey G. Towell, Mark W. Craven, Jude W. Shavlik

NeurIPS 1991 Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules Geoffrey Towell, Jude W. Shavlik

ICML 1991 Refining Domain Theories Expressed as Finite-State Automata Richard Maclin, Jude W. Shavlik

NeurIPS 1991 Refining PID Controllers Using Neural Networks Gary M. Scott, Jude W. Shavlik, W. Harmon Ray

MLJ 1991 Symbolic and Neural Learning Algorithms: An Experimental Comparison Jude W. Shavlik, Raymond J. Mooney, Geoffrey G. Towell

MLJ 1990 Acquiring Recursive and Iterative Concepts with Explanation-Based Learning Jude W. Shavlik

AAAI 1990 Refinement ofApproximate Domain Theories by Knowledge-Based Neural Networks Geoffrey G. Towell, Jude W. Shavlik, Michiel O. Noordewier

NeurIPS 1990 Training Knowledge-Based Neural Networks to Recognize Genes in DNA Sequences Michiel O. Noordewier, Geoffrey G. Towell, Jude W. Shavlik

IJCAI 1989 Acquiring Recursive Concepts with Explanation-Based Learning Jude W. Shavlik

ICML 1989 An Empirical Analysis of EBL Approaches for Learning Plan Schemata Jude W. Shavlik

IJCAI 1989 An Experimental Comparison of Symbolic and Connectionist Learning Algorithms Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. Towell, Alan Gove

ICML 1989 Combining Explanation-Based Learning and Artificial Neural Networks Jude W. Shavlik, Geoffrey G. Towell

ICML 1989 Enriching Vocabularies by Generalizing Explanation Structures Richard Maclin, Jude W. Shavlik

ICML 1989 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

IJCAI 1987 An Explanation-Based Approach to Generalizing Number Jude W. Shavlik, Gerald DeJong

AAAI 1987 BAGGER: An EBL System That Extends and Generalizes Explanations Jude W. Shavlik, Gerald DeJong

IJCAI 1985 Learning About Momentum Conservation Jude W. Shavlik