Learning about Momentum Conservation. - Jude W. Shavlik (IJCAI, 1985)

Computer understanding and generalization of symbolic mathematical calculations: a case study in physics problem solving. - Jude W. Shavlik; Gerald DeJong (SYMSAC, 1986)

BAGGER: An EBL System that Extends and Generalizes Explanations. - Jude W. Shavlik; Gerald DeJong (AAAI, 1987)

An Explanation-based Approach to Generalizing Number. - Jude W. Shavlik; Gerald DeJong (IJCAI, 1987)

Generalizing the Structure of Explanations in Explanation-Based Learning - Jude W. Shavlik (1988)

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 (ML, 1989)

Enriching Vocabularies by Generalizing Explanation Structures. - Richard Maclin; Jude W. Shavlik (ML, 1989)

An Empirical Analysis of EBL Approaches for Learning Plan Schemata. - Jude W. Shavlik (ML, 1989)

Combining Explanation-Based Learning and Artificial Neural Networks. - Jude W. Shavlik; Geoffrey G. Towell (ML, 1989)

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

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

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

Training Knowledge-Based Neural Networks to Recognize Genes. - Michiel O. Noordewier; Geoffrey G. Towell; Jude W. Shavlik (NIPS, 1990)

Learning in Mathematically-Based Domains: Understanding and Generalizing Obstacle Cancellations. - Jude W. Shavlik; Gerald DeJong (Artif. Intell., 1990)

Acquiring Recursive and Iterative Concepts with Explanation-Based Learning. - Jude W. Shavlik (Mach. Learn., 1990)

Refining Domain Theories Expressed as Finite-State Automata. - Richard Maclin; Jude W. Shavlik (ML, 1991)

Constructive Induction in Knowledge-Based Neural Networks. - Geoffrey G. Towell; Mark W. Craven; Jude W. Shavlik (ML, 1991)

Refined PID Controllers Using Neural Networks. - Gary M. Scott; Jude W. Shavlik; W. Harmon Ray (NIPS, 1991)

Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules. - Geoffrey G. Towell; Jude W. Shavlik (NIPS, 1991)

Symbolic and Neural Learning Algorithms: An Experimental Comparison. - Jude W. Shavlik; Raymond J. Mooney; Geoffrey G. Towell (Mach. Learn., 1991)

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

Visualizing Learning and Computation in Artificial Neural Networks. - Mark W. Craven; Jude W. Shavlik (Int. J. Artif. Intell. Tools, 1992)

Refining PID Controllers Using Neural Networks. - Gary M. Scott; Jude W. Shavlik; W. Harmon Ray (Neural Comput., 1992)

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

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

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

Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools. - Kevin J. Cherkauer; Jude W. Shavlik (ISMB, 1993)

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

Extracting Refined Rules from Knowledge-Based Neural Networks. - Geoffrey G. Towell; Jude W. Shavlik (Mach. Learn., 1993)

Incorporating Advice into Agents that Learn from Reinforcements. - Richard Maclin; Jude W. Shavlik (AAAI, 1994)

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

Using Genetic Search to Refine Knowledge-based Neural Networks. - David W. Opitz; Jude W. Shavlik (ICML, 1994)

Knowledge-Based Artificial Neural Networks. - Geoffrey G. Towell; Jude W. Shavlik (Artif. Intell., 1994)

The First International Conference on Intelligent Systems for Molecular Biology. - David B. Searls; Jude W. Shavlik; Lawrence Hunter (AI Mag., 1994)

Machine Learning Approaches to Gene Recognition. - Mark W. Craven; Jude W. Shavlik (IEEE Expert, 1994)

Combining Symbolic and Neural Learning. - Jude W. Shavlik (Mach. Learn., 1994)

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

Rapid Quality Estimation of Neural Network Input Representations. - Kevin J. Cherkauer; Jude W. Shavlik (NIPS, 1995)

Extracting Tree-Structured Representations of Trained Networks. - Mark W. Craven; Jude W. Shavlik (NIPS, 1995)

Generating Accurate and Diverse Members of a Neural-Network Ensemble. - David W. Opitz; Jude W. Shavlik (NIPS, 1995)

Dynamically adding symbolically meaningful nodes to knowledge-based neural networks. - David W. Opitz; Jude W. Shavlik (Knowl. Based Syst., 1995)

Introduction. - Jude W. Shavlik; Lawrence Hunter; David B. Searls (Mach. Learn., 1995)

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 (ISMB, 1996)

Growing Simpler Decision Trees to Facilitate Knowledge Discovery. - Kevin J. Cherkauer; Jude W. Shavlik (KDD, 1996)

Actively Searching for an Effective Neural Network Ensemble. - David W. Opitz; Jude W. Shavlik (Connect. Sci., 1996)

Creating Advice-Taking Reinforcement Learners. - Richard Maclin; Jude W. Shavlik (Mach. Learn., 1996)

Using neural networks to automatically refine expert system knowledge bases: experiments in the NYNEX MAX domain. - David W. Opitz; Mark W. Craven; Jude W. Shavlik (ICNN, 1997)

Increasing Consensus Accuracy in DNA Fragment Assemblies by Incorporating Fluorescent Trace Representations. - Carolyn F. Allex; Schuyler F. Baldwin; Jude W. Shavlik; Frederick R. Blattner (ISMB, 1997)

Using neural networks for data mining. - Mark W. Craven; Jude W. Shavlik (Future Gener. Comput. Syst., 1997)

Understanding Time-Series Networks: A Case Study in Rule Extraction. - Mark W. Craven; Jude W. Shavlik (Int. J. Neural Syst., 1997)

Connectionist Theory Refinement: Genetically Searching the Space of Network Topologies. - David W. Opitz; Jude W. Shavlik (J. Artif. Intell. Res., 1997)

Creating Advice-Taking Reinforcement Learners. - Richard Maclin; Jude W. Shavlik (Learning to Learn, 1998)

Bridging Science and Applications (Panel). - Jude W. Shavlik; Lawrence Birnbaum; William R. Swartout; Eric Horvitz; Barbara Hayes-Roth (IUI, 1999)

An Instructable, Adaptive Interface for Discovering and Monitoring Information on the World-Wide Web. - Jude W. Shavlik; Susan Calcari; Tina Eliassi-Rad; Jack Solock (IUI, 1999)

Neural network input representations that produce accurate consensus sequences from DNA fragment assemblies. - Carolyn F. Allex; Jude W. Shavlik; Frederick R. Blattner (Bioinform., 1999)

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, 2000)

A Probabilistic Learning Approach to Whole-Genome Operon Prediction. - Mark W. Craven; David Page; Jude W. Shavlik; Joseph Bockhorst; Jeremy D. Glasner (ISMB, 2000)

Learning users' interests by unobtrusively observing their normal behavior. - Jeremy Goecks; Jude W. Shavlik (IUI, 2000)

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

An Empirical Evaluation of Bagging in Inductive Logic Programming. - Inês de Castro Dutra; David Page; Vítor Santos Costa; Jude W. Shavlik (ILP, 2002)

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 (ISMB, 2002)

Knowledge-Based Support Vector Machine Classifiers. - Glenn Fung; Olvi L. Mangasarian; Jude W. Shavlik (NIPS, 2002)

Report on the First International Conference on Knowledge Capture (K-CAP). - Yolanda Gil; Mark A. Musen; Jude W. Shavlik (AI Mag., 2002)

Interpreting microarray expression data using text annotating the genes. - Michael Molla; Peter Andreae; Jeremy D. Glasner; Frederick R. Blattner; Jude W. Shavlik (Inf. Sci., 2002)

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

Toward Automatic Management of Embarrassingly Parallel Applications. - Inês de Castro Dutra; David Page; Vítor Santos Costa; Jude W. Shavlik; Michael Waddell (Euro-Par, 2003)

Applying Theory Revision to the Design of Distributed Databases. - Fernanda Araújo Baião; Marta Mattoso; Jude W. Shavlik; Gerson Zaverucha (ILP, 2003)

A Bayesian Network Approach to Operon Prediction. - Joseph Bockhorst; Mark W. Craven; David Page; Jude W. Shavlik; Jeremy D. Glasner (Bioinform., 2003)

A System for Building Intelligent Agents that Learn to Retrieve and Extract Information. - Tina Eliassi-Rad; Jude W. Shavlik (User Model. User Adapt. Interact., 2003)

Intelligent Web Agents that Learn to Retrieve and Extract Information. - Tina Eliassi-Rad; Jude W. Shavlik (Intelligent Exploration of the Web, 2003)

A Self-Tuning Method for One-Chip SNP Identification. - Michael Molla; Jude W. Shavlik; Thomas Albert 001; Todd Richmond; Steven Smith (CSB, 2004)

Learning an Approximation to Inductive Logic Programming Clause Evaluation. - Frank DiMaio; Jude W. Shavlik (ILP, 2004)

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 (ILP, 2004)

Scaling Up ILP: Experiences with Extracting Relations from Biomedical Text. - Jude W. Shavlik (ILP, 2004)

Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage. - Jude W. Shavlik; Mark Shavlik (KDD, 2004)

Pictorial Structures for Molecular Modeling: Interpreting Density Maps. - Frank DiMaio; Jude W. Shavlik; George N. Phillips (NIPS, 2004)

Using Machine Learning to Design and Interpret Gene-Expression Microarrays. - Michael Molla; Michael Waddell; David Page; Jude W. Shavlik (AI Mag., 2004)

Knowledge-Based Kernel Approximation. - Olvi L. Mangasarian; Jude W. Shavlik; Edward W. Wild (J. Mach. Learn. Res., 2004)

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 (AAAI, 2005)

Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another. - Lisa Torrey; Trevor Walker; Jude W. Shavlik; Richard Maclin (ECML, 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 001; Vítor Santos Costa; Jude W. Shavlik (IJCAI, 2005)

A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment. - Héctor Corrada Bravo; David Page; Raghu Ramakrishnan 001; Jude W. Shavlik; Vítor Santos Costa (ILP, 2005)

Knowledge transfer via advice taking. - Lisa Torrey; Trevor Walker; Jude W. Shavlik; Richard Maclin (K-CAP, 2005)

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

Skill Acquisition Via Transfer Learning and Advice Taking. - Lisa Torrey; Jude W. Shavlik; Trevor Walker; Richard Maclin (ECML, 2006)

Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition. - Frank DiMaio; Jude W. Shavlik (ICDM, 2006)

A probabilistic approach to protein backbone tracing in electron density maps. - Frank DiMaio; Jude W. Shavlik; George N. Phillips (ISMB (Supplement of Bioinformatics), 2006)

Bellwether Analysis: Predicting Global Aggregates from Local Regions. - Bee-Chung Chen; Raghu Ramakrishnan 001; Jude W. Shavlik; Pradeep Tamma (VLDB, 2006)

Gleaner: Creating ensembles of first-order clauses to improve recall-precision curves. - Mark H. Goadrich; Louis Oliphant; Jude W. Shavlik (Mach. Learn., 2006)

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, 2007)

Improved Methods for Template-Matching in Electron-Density Maps Using Spherical Harmonics. - Frank DiMaio; Ameet Soni; George N. Phillips; Jude W. Shavlik (BIBM, 2007)

Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates. - Mark H. Goadrich; Jude W. Shavlik (ILP, 2007)

Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming. - Louis Oliphant; Jude W. Shavlik (ILP, 2007)

Relational Macros for Transfer in Reinforcement Learning. - Lisa Torrey; Jude W. Shavlik; Trevor Walker; Richard Maclin (ILP, 2007)

Building Relational World Models for Reinforcement Learning. - Trevor Walker; Lisa Torrey; Jude W. Shavlik; Richard Maclin (ILP, 2007)

Creating protein models from electron-density maps using particle-filtering methods. - Frank DiMaio; Dmitry A. Kondrashov; Eduard Bitto; Ameet Soni; Craig A. Bingman; George N. Phillips Jr.; Jude W. Shavlik (Bioinform., 2007)

Advice Taking and Transfer Learning: Naturally Inspired Extensions to Reinforcement Learning. - Lisa Torrey; Trevor Walker; Richard Maclin; Jude W. Shavlik (AAAI Fall Symposium: Naturally-Inspired Artificial Intelligence, 2008)

Guest editors' introduction: special issue on inductive logic programming (ILP-2007). - Hendrik Blockeel; Jude W. Shavlik; Prasad Tadepalli (Mach. Learn., 2008)

Rule Extraction for Transfer Learning. - Lisa Torrey; Jude W. Shavlik; Trevor Walker; Richard Maclin (Rule Extraction from Support Vector Machines, 2008)

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 (ICDM Workshops, 2009)

Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule. - Sriraam Natarajan; Prasad Tadepalli; Gautam Kunapuli; Jude W. Shavlik (ICMLA, 2009)

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

Boosting First-Order Clauses for Large, Skewed Data Sets. - Louis Oliphant; Elizabeth S. Burnside; Jude W. Shavlik (ILP, 2009)

Policy Transfer via Markov Logic Networks. - Lisa Torrey; Jude W. Shavlik (ILP, 2009)

Anytime Lifted Belief Propagation. - Rodrigo de Salvo Braz; Sriraam Natarajan; Hung Bui 001; Jude W. Shavlik; Stuart Russell 001 (MLG/SRL@ILP, 2009)

Knowledge Intensive Learning - Directed vs Undirected SRL Models. - Sriraam Natarajan; Prasad Tadepalli; Gautam Kunapuli; Jude W. Shavlik (MLG/SRL@ILP, 2009)

Spherical-harmonic decomposition for molecular recognition in electron-density maps. - Frank DiMaio; Ameet Soni; George N. Phillips; Jude W. Shavlik (Int. J. Data Min. Bioinform., 2009)

Bellwether analysis: Searching for cost-effective query-defined predictors in large databases. - Bee-Chung Chen; Raghu Ramakrishnan 001; Jude W. Shavlik; Pradeep Tamma (ACM Trans. Knowl. Discov. Data, 2009)

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 (StarAI@AAAI, 2010)

Guiding belief propagation using domain knowledge for protein-structure determination. - Ameet Soni; Craig A. Bingman; Jude W. Shavlik (BCB, 2010)

Multi-Agent Inverse Reinforcement Learning. - Sriraam Natarajan; Gautam Kunapuli; Kshitij Judah; Prasad Tadepalli; Kristian Kersting; Jude W. Shavlik (ICMLA, 2010)

Uncovering age-specific invasive and DCIS breast cancer rules using inductive logic programming. - Houssam Nassif; David Page; Mehmet Ayvaci; Jude W. Shavlik; Elizabeth S. Burnside (IHI, 2010)

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 (ILP, 2010)

Online Knowledge-Based Support Vector Machines. - Gautam Kunapuli; Kristin P. Bennett; Amina Shabbeer; Richard Maclin; Jude W. Shavlik (ECML/PKDD (2), 2010)

Validation of Results from Knowledge Discovery: Mass Density as a Predictor of Breast Cancer. - Ryan W. Woods; Louis Oliphant; Kazuhiko Shinki; David Page; Jude W. Shavlik; Elizabeth S. Burnside (J. Digit. Imaging, 2010)

Transfer Learning via Advice Taking. - Lisa Torrey; Jude W. Shavlik; Trevor Walker; Richard Maclin (Advances in Machine Learning I, 2010)

Learning Markov Logic Networks via Functional Gradient Boosting. - Tushar Khot; Sriraam Natarajan; Kristian Kersting; Jude W. Shavlik (ICDM, 2011)

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

Integrating knowledge capture and supervised learning through a human-computer interface. - Trevor Walker; Gautam Kunapuli; Noah Larsen; David Page; Jude W. Shavlik (K-CAP, 2011)

Advice Refinement in Knowledge-Based SVMs. - Gautam Kunapuli; Richard Maclin; Jude W. Shavlik (NIPS, 2011)

Felix: Scaling Inference for Markov Logic with an Operator-based Approach - Feng Niu; Ce Zhang 001; Christopher Ré; Jude W. Shavlik (CoRR, 2011)

Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS. - Feng Niu; Christopher Ré; AnHai Doan; Jude W. Shavlik (Proc. VLDB Endow., 2011)

Predictive Models in Personalized Medicine: Neural Information Processing Systems (NIPS), 2010 workshop report. - Faisal Farooq; Balaji Krishnapuram; Rómer Rosales; Shipeng Yu; Jude W. Shavlik; Raju Kucherlapati (SIGHIT Rec., 2011)

Invited Talks. - Timothy W. Clark; William W. Cohen; Lawrence Hunter; Chris J. Lintott; Jude W. Shavlik (AAAI Fall Symposium: Discovery Informatics, 2012)

Big Data versus the Crowd: Looking for Relationships in All the Right Places. - Ce Zhang 001; Feng Niu; Christopher Ré; Jude W. Shavlik (ACL (1), 2012)

Scaling Inference for Markov Logic via Dual Decomposition. - Feng Niu; Ce Zhang 001; Christopher Ré; Jude W. Shavlik (ICDM, 2012)

Twenty-Five Years of Combining Symbolic and Numeric Learning. - Jude W. Shavlik (NeSy@AAAI, 2012)

Mirror Descent for Metric Learning: A Unified Approach. - Gautam Kunapuli; Jude W. Shavlik (ECML/PKDD (1), 2012)

Learning Relational Structure for Temporal Relation Extraction. - Tushar Khot; Siddharth Srivastava 001; Sriraam Natarajan; Jude W. Shavlik (StarAI@UAI, 2012)

DeepDive: Web-scale Knowledge-base Construction using Statistical Learning and Inference. - Feng Niu; Ce Zhang 001; Christopher Ré; Jude W. Shavlik (VLDS, 2012)

Elementary: Large-Scale Knowledge-Base Construction via Machine Learning and Statistical Inference. - Feng Niu; Ce Zhang 001; Christopher Ré; Jude W. Shavlik (Int. J. Semantic Web Inf. Syst., 2012)

Probabilistic Ensembles for Improved Inference in protein-Structure Determination. - Ameet Soni; Jude W. Shavlik (J. Bioinform. Comput. Biol., 2012)

Gradient-based boosting for statistical relational learning: The relational dependency network case. - Sriraam Natarajan; Tushar Khot; Kristian Kersting; Bernd Gutmann; Jude W. Shavlik (Mach. Learn., 2012)

Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text. - Sriraam Natarajan; Jose Picado; Tushar Khot; Kristian Kersting; Christopher Ré; Jude W. Shavlik (StarAI@AAAI, 2013)

Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms. - Jie Liu 006; David Page; Houssam Nassif; Jude W. Shavlik; Peggy L. Peissig; Catherine A. McCarty; Adedayo A. Onitilo; Elizabeth S. Burnside (AMIA, 2013)

Using machine learning to identify benign cases with non-definitive biopsy. - Finn Kuusisto; Inês de Castro Dutra; Houssam Nassif; Yirong Wu; Molly E. Klein; Heather B. Neuman; Jude W. Shavlik; Elizabeth S. Burnside (Healthcom, 2013)

Guiding Autonomous Agents to Better Behaviors through Human Advice. - Gautam Kunapuli; Phillip Odom; Jude W. Shavlik; Sriraam Natarajan (ICDM, 2013)

Uplift Modeling with ROC: An SRL Case Study. - Houssam Nassif; Finn Kuusisto; Elizabeth S. Burnside; Jude W. Shavlik (ILP (Late Breaking Papers), 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 (ECML/PKDD (3), 2013)

Bootstrapping Knowledge Base Acceleration. - Tushar Khot; Ce Zhang 001; Jude W. Shavlik; Sriraam Natarajan; Christopher Ré (TREC, 2013)

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

Classification from One Class of Examples for Relational Domains. - Tushar Khot; Sriraam Natarajan; Jude W. Shavlik (StarAI@AAAI, 2014)

Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge. - Sriraam Natarajan; Jose Picado; Tushar Khot; Kristian Kersting; Christopher Ré; Jude W. Shavlik (ILP, 2014)

Support Vector Machines for Differential Prediction. - Finn Kuusisto; Vítor Santos Costa; Houssam Nassif; Elizabeth S. Burnside; David Page; Jude W. Shavlik (ECML/PKDD (2), 2014)

Detecting Semantic Uncertainty by Learning Hedge Cues in Sentences Using an HMM. - Xiujun Li; Wei Gao; Jude W. Shavlik (SMIR@SIGIR, 2014)

Corleone: hands-off crowdsourcing for entity matching. - Chaitanya Gokhale; Sanjib Das; AnHai Doan; Jeffrey F. Naughton; Narasimhan Rampalli; Jude W. Shavlik; Xiaojin Zhu 001 (SIGMOD Conference, 2014)

Boosted Statistical Relational Learners - From Benchmarks to Data-Driven Medicine - Sriraam Natarajan; Kristian Kersting; Tushar Khot; Jude W. Shavlik (Springer, 2014)

Anomaly Detection in Text: The Value of Domain Knowledge. - Raksha Kumaraswamy; Anurag Wazalwar; Tushar Khot; Jude W. Shavlik; Sriraam Natarajan (FLAIRS, 2015)

TAC KBP 2015 : English Slot Filling Track Relational Learning with Expert Advice. - Dileep Viswanathan; Anurag Wazalwar; Sriraam Natarajan; Ameet Soni; Jude W. Shavlik (TAC, 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 (Mach. Learn., 2015)

Learning Relational Dependency Networks for Relation Extraction. - Ameet Soni; Dileep Viswanathan; Jude W. Shavlik; Sriraam Natarajan (ILP, 2016)

A Recap of Early Work on Theory and Knowledge Refinement. - Raymond J. Mooney; Jude W. Shavlik (AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering, 2021)