Jude W. Shavlik

Publication Activity (10 Years)

Years Active: 1985-2021
Publications (10 Years): 3

Top Venues

AAAI Workshop: Statistical Relational Artificial Intelligence

ILP

Mach. Learn.

ILP (Late Breaking Papers)

Publications

Raymond J. Mooney, Jude W. Shavlik
A Recap of Early Work on Theory and Knowledge Refinement. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Ameet Soni, Dileep Viswanathan, Jude W. Shavlik, Sriraam Natarajan
Learning Relational Dependency Networks for Relation Extraction. ILP (2016)
Dileep Viswanathan, Ameet Soni, Jude W. Shavlik, Sriraam Natarajan
Learning Relational Dependency Networks for Relation Extraction. CoRR (2016)
Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik
Gradient-based boosting for statistical relational learning: the Markov logic network and missing data cases. Mach. Learn. 100 (1) (2015)
Raksha Kumaraswamy, Anurag Wazalwar, Tushar Khot, Jude W. Shavlik, Sriraam Natarajan
Anomaly Detection in Text: The Value of Domain Knowledge. FLAIRS Conference (2015)
Dileep Viswanathan, Anurag Wazalwar, Sriraam Natarajan, Ameet Soni, Jude W. Shavlik
TAC KBP 2015 : English Slot Filling Track Relational Learning with Expert Advice. TAC (2015)
Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher Ré, Jude W. Shavlik
Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge. ILP (2014)
Finn Kuusisto, Vítor Santos Costa, Houssam Nassif, Elizabeth S. Burnside, David Page, Jude W. Shavlik
Support Vector Machines for Differential Prediction. ECML/PKDD (2) (2014)
Xiujun Li, Wei Gao, Jude W. Shavlik
Detecting Semantic Uncertainty by Learning Hedge Cues in Sentences Using an HMM. SMIR@SIGIR (2014)
Chaitanya Gokhale, Sanjib Das, AnHai Doan, Jeffrey F. Naughton, Narasimhan Rampalli, Jude W. Shavlik, Xiaojin Zhu
Corleone: hands-off crowdsourcing for entity matching. SIGMOD Conference (2014)
Tushar Khot, Sriraam Natarajan, Jude W. Shavlik
Classification from One Class of Examples for Relational Domains. AAAI Workshop: Statistical Relational Artificial Intelligence (2014)
Tushar Khot, Sriraam Natarajan, Jude W. Shavlik
Relational One-Class Classification: A Non-Parametric Approach. AAAI (2014)
Gautam Kunapuli, Phillip Odom, Jude W. Shavlik, Sriraam Natarajan
Guiding Autonomous Agents to Better Behaviors through Human Advice. ICDM (2013)
Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, Jude W. Shavlik
Uplift Modeling with ROC: An SRL Case Study. ILP (Late Breaking Papers) (2013)
Jie Liu, David Page, Houssam Nassif, Jude W. Shavlik, Peggy L. Peissig, Catherine A. McCarty, Adedayo A. Onitilo, Elizabeth S. Burnside
Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms. AMIA (2013)
Tushar Khot, Ce Zhang, Jude W. Shavlik, Sriraam Natarajan, Christopher Ré
Bootstrapping Knowledge Base Acceleration. TREC (2013)
Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, David Page, Jude W. Shavlik, Vítor Santos Costa
Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling. ECML/PKDD (3) (2013)
Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher Ré, Jude W. Shavlik
Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text. AAAI Workshop: Statistical Relational Artificial Intelligence (2013)
Finn Kuusisto, Inês de Castro Dutra, Houssam Nassif, Yirong Wu, Molly E. Klein, Heather B. Neuman, Jude W. Shavlik, Elizabeth S. Burnside
Using machine learning to identify benign cases with non-definitive biopsy. Healthcom (2013)
Gautam Kunapuli, Jude W. Shavlik
Mirror Descent for Metric Learning: A Unified Approach. ECML/PKDD (1) (2012)
Ameet Soni, Jude W. Shavlik
Probabilistic Ensembles for Improved Inference in protein-Structure Determination. J. Bioinform. Comput. Biol. 10 (1) (2012)
Feng Niu, Ce Zhang, Christopher Ré, Jude W. Shavlik
Elementary: Large-Scale Knowledge-Base Construction via Machine Learning and Statistical Inference. Int. J. Semantic Web Inf. Syst. 8 (3) (2012)
Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann, Jude W. Shavlik
Gradient-based boosting for statistical relational learning: The relational dependency network case. Mach. Learn. 86 (1) (2012)
Ce Zhang, Feng Niu, Christopher Ré, Jude W. Shavlik
Big Data versus the Crowd: Looking for Relationships in All the Right Places. ACL (1) (2012)
Timothy W. Clark, William W. Cohen, Lawrence Hunter, Chris J. Lintott, Jude W. Shavlik
Invited Talks. AAAI Fall Symposium: Discovery Informatics (2012)
Jude W. Shavlik
Twenty-Five Years of Combining Symbolic and Numeric Learning. NeSy@AAAI (2012)
Tushar Khot, Siddharth Srivastava, Sriraam Natarajan, Jude W. Shavlik
Learning Relational Structure for Temporal Relation Extraction. StarAI@UAI (2012)
Feng Niu, Ce Zhang, Christopher Ré, Jude W. Shavlik
Scaling Inference for Markov Logic via Dual Decomposition. ICDM (2012)
Feng Niu, Ce Zhang, Christopher Ré, Jude W. Shavlik
DeepDive: Web-scale Knowledge-base Construction using Statistical Learning and Inference. VLDS (2012)
Gautam Kunapuli, Richard Maclin, Jude W. Shavlik
Advice Refinement in Knowledge-Based SVMs. NIPS (2011)
Sriraam Natarajan, Saket Joshi, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik
Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach. IJCAI (2011)
Feng Niu, Ce Zhang, Christopher Ré, Jude W. Shavlik
Felix: Scaling Inference for Markov Logic with an Operator-based Approach CoRR (2011)
Faisal Farooq, Balaji Krishnapuram, Rómer Rosales, Shipeng Yu, Jude W. Shavlik, Raju Kucherlapati
Predictive Models in Personalized Medicine: Neural Information Processing Systems (NIPS), 2010 workshop report. SIGHIT Rec. 1 (1) (2011)
Feng Niu, Christopher Ré, AnHai Doan, Jude W. Shavlik
Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS. Proc. VLDB Endow. 4 (6) (2011)
Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik
Learning Markov Logic Networks via Functional Gradient Boosting. ICDM (2011)
Trevor Walker, Gautam Kunapuli, Noah Larsen, David Page, Jude W. Shavlik
Integrating knowledge capture and supervised learning through a human-computer interface. K-CAP (2011)
Ameet Soni, Jude W. Shavlik
Probabilistic ensembles for improved inference in protein-structure determination. BCB (2011)
Feng Niu, Christopher Ré, AnHai Doan, Jude W. Shavlik
Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS CoRR (2011)
Ryan W. Woods, Louis Oliphant, Kazuhiko Shinki, David Page, Jude W. Shavlik, Elizabeth S. Burnside
Validation of Results from Knowledge Discovery: Mass Density as a Predictor of Breast Cancer. J. Digit. Imaging 23 (5) (2010)
Houssam Nassif, David Page, Mehmet Ayvaci, Jude W. Shavlik, Elizabeth S. Burnside
Uncovering age-specific invasive and DCIS breast cancer rules using inductive logic programming. IHI (2010)
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. ECML/PKDD (2) (2010)
Gautam Kunapuli, Kristin P. Bennett, Amina Shabbeer, Richard Maclin, Jude W. Shavlik
Online Knowledge-Based Support Vector Machines. ECML/PKDD (2) (2010)
Ameet Soni, Craig A. Bingman, Jude W. Shavlik
Guiding belief propagation using domain knowledge for protein-structure determination. BCB (2010)
Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik
Multi-Agent Inverse Reinforcement Learning. ICMLA (2010)
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. Statistical Relational Artificial Intelligence (2010)
Trevor Walker, Ciaran O'Reilly, Gautam Kunapuli, Sriraam Natarajan, Richard Maclin, David Page, Jude W. Shavlik
Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge. ILP (2010)
Jude W. Shavlik, Sriraam Natarajan
Speeding Up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network. IJCAI (2009)
Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapuli, Jude W. Shavlik
Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule. ICMLA (2009)
Bee-Chung Chen, Raghu Ramakrishnan, Jude W. Shavlik, Pradeep Tamma
Bellwether analysis: Searching for cost-effective query-defined predictors in large databases. ACM Trans. Knowl. Discov. Data 3 (1) (2009)
Louis Oliphant, Elizabeth S. Burnside, Jude W. Shavlik
Boosting First-Order Clauses for Large, Skewed Data Sets. ILP (2009)
Frank DiMaio, Ameet Soni, George N. Phillips, Jude W. Shavlik
Spherical-harmonic decomposition for molecular recognition in electron-density maps. Int. J. Data Min. Bioinform. 3 (2) (2009)
Lisa Torrey, Jude W. Shavlik
Policy Transfer via Markov Logic Networks. ILP (2009)
Houssam Nassif, Ryan W. Woods, Elizabeth S. Burnside, Mehmet Ayvaci, Jude W. Shavlik, David Page
Information Extraction for Clinical Data Mining: A Mammography Case Study. ICDM Workshops (2009)
Hendrik Blockeel, Jude W. Shavlik, Prasad Tadepalli
Guest editors' introduction: special issue on inductive logic programming (ILP-2007). Mach. Learn. 73 (1) (2008)
Lisa Torrey, Trevor Walker, Richard Maclin, Jude W. Shavlik
Advice Taking and Transfer Learning: Naturally Inspired Extensions to Reinforcement Learning. AAAI Fall Symposium: Naturally-Inspired Artificial Intelligence (2008)
Louis Oliphant, Jude W. Shavlik
Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming. ILP (2007)
Richard Maclin, Edward W. Wild, Jude W. Shavlik, Lisa Torrey, Trevor Walker
Refining Rules Incorporated into Knowledge-Based Support Vector Learners Via Successive Linear Programming. AAAI (2007)
Frank DiMaio, Dmitry A. Kondrashov, Eduard Bitto, Ameet Soni, Craig A. Bingman, George N. Phillips Jr., Jude W. Shavlik
Creating protein models from electron-density maps using particle-filtering methods. Bioinform. 23 (21) (2007)
Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin
Relational Macros for Transfer in Reinforcement Learning. ILP (2007)
Frank DiMaio, Ameet Soni, George N. Phillips, Jude W. Shavlik
Improved Methods for Template-Matching in Electron-Density Maps Using Spherical Harmonics. BIBM (2007)
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richard Maclin
Building Relational World Models for Reinforcement Learning. ILP (2007)
Mark Goadrich, Jude W. Shavlik
Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates. ILP (2007)
Richard Maclin, Jude W. Shavlik, Trevor Walker, Lisa Torrey
A Simple and Effective Method for Incorporating Advice into Kernel Methods. AAAI (2006)
Frank DiMaio, Jude W. Shavlik
Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition. ICDM (2006)
Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin
Skill Acquisition Via Transfer Learning and Advice Taking. ECML (2006)
Bee-Chung Chen, Raghu Ramakrishnan, Jude W. Shavlik, Pradeep Tamma
Bellwether Analysis: Predicting Global Aggregates from Local Regions. VLDB (2006)
Mark Goadrich, Louis Oliphant, Jude W. Shavlik
Gleaner: Creating ensembles of first-order clauses to improve recall-precision curves. Mach. Learn. 64 (1-3) (2006)
Frank DiMaio, Jude W. Shavlik, George N. Phillips
A probabilistic approach to protein backbone tracing in electron density maps. ISMB (Supplement of Bioinformatics) (2006)
Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richard Maclin
Knowledge transfer via advice taking. K-CAP (2005)
Héctor Corrada Bravo, David Page, Raghu Ramakrishnan, Jude W. Shavlik, Vítor Santos Costa
A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment. ILP (2005)
Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richard Maclin
Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another. ECML (2005)
Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Raghu Ramakrishnan, Vítor Santos Costa, Jude W. Shavlik
View Learning for Statistical Relational Learning: With an Application to Mammography. IJCAI (2005)
Richard Maclin, Jude W. Shavlik, Lisa Torrey, Trevor Walker, Edward W. Wild
Giving Advice about Preferred Actions to Reinforcement Learners Via Knowledge-Based Kernel Regression. AAAI (2005)
Frank DiMaio, Jude W. Shavlik
Learning an Approximation to Inductive Logic Programming Clause Evaluation. ILP (2004)
Michael Molla, Michael Waddell, David Page, Jude W. Shavlik
Using Machine Learning to Design and Interpret Gene-Expression Microarrays. AI Mag. 25 (1) (2004)
Michael Molla, Jude W. Shavlik, Thomas Albert, Todd Richmond, Steven Smith
A Self-Tuning Method for One-Chip SNP Identification. CSB (2004)
Jude W. Shavlik, Mark Shavlik
Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage. KDD (2004)
Olvi L. Mangasarian, Jude W. Shavlik, Edward W. Wild
Knowledge-Based Kernel Approximation. J. Mach. Learn. Res. 5 (2004)
Mark Goadrich, Louis Oliphant, Jude W. Shavlik
Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction. ILP (2004)
Frank DiMaio, Jude W. Shavlik, George N. Phillips
Pictorial Structures for Molecular Modeling: Interpreting Density Maps. NIPS (2004)
Jude W. Shavlik
Scaling Up ILP: Experiences with Extracting Relations from Biomedical Text. ILP (2004)
Tina Eliassi-Rad, Jude W. Shavlik
A System for Building Intelligent Agents that Learn to Retrieve and Extract Information. User Model. User Adapt. Interact. 13 (1-2) (2003)
Fernanda Araujo Baião, Marta Mattoso, Jude W. Shavlik, Gerson Zaverucha
Applying Theory Revision to the Design of Distributed Databases. ILP (2003)
Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik
Knowledge-Based Nonlinear Kernel Classifiers. COLT (2003)
Joseph Bockhorst, Mark W. Craven, David Page, Jude W. Shavlik, Jeremy D. Glasner
A Bayesian Network Approach to Operon Prediction. Bioinform. 19 (10) (2003)
Inês de Castro Dutra, David Page, Vítor Santos Costa, Jude W. Shavlik, Michael Waddell
Toward Automatic Management of Embarrassingly Parallel Applications. Euro-Par (2003)
Inês de Castro Dutra, David Page, Vítor Santos Costa, Jude W. Shavlik
An Empirical Evaluation of Bagging in Inductive Logic Programming. ILP (2002)
Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik
Knowledge-Based Support Vector Machine Classifiers. NIPS (2002)
Yolanda Gil, Mark A. Musen, Jude W. Shavlik
Report on the First International Conference on Knowledge Capture (K-CAP). AI Mag. 23 (4) (2002)
Michael Molla, Peter Andreae, Jeremy D. Glasner, Frederick R. Blattner, Jude W. Shavlik
Interpreting microarray expression data using text annotating the genes. Inf. Sci. 146 (1-4) (2002)
Michael Molla, Peter Andreae, Jeremy D. Glasner, Frederick R. Blattner, Jude W. Shavlik
Interpreting Microarray Expression Data Using Text Annotating the Genes. JCIS (2002)
J. B. Tobler, Michael Molla, Emile F. Nuwaysir, R. D. Green, Jude W. Shavlik
Evaluating machine learning approaches for aiding probe selection for gene-expression arrays. ISMB (2002)
Tina Eliassi-Rad, Jude W. Shavlik
A Theory-Refinement Approach to Information Extraction. ICML (2001)
Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner
Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes. ICML (2000)
Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner
A Probabilistic Learning Approach to Whole-Genome Operon Prediction. ISMB (2000)
Jeremy Goecks, Jude W. Shavlik
Learning users' interests by unobtrusively observing their normal behavior. IUI (2000)
Jude W. Shavlik, Susan Calcari, Tina Eliassi-Rad, Jack Solock
An Instructable, Adaptive Interface for Discovering and Monitoring Information on the World-Wide Web. IUI (1999)
Carolyn F. Allex, Jude W. Shavlik, Frederick R. Blattner
Neural network input representations that produce accurate consensus sequences from DNA fragment assemblies. Bioinform. 15 (9) (1999)
Jude W. Shavlik, Lawrence Birnbaum, William R. Swartout, Eric Horvitz, Barbara Hayes-Roth
Bridging Science and Applications (Panel). IUI (1999)
Mark W. Craven, Jude W. Shavlik
Understanding Time-Series Networks: A Case Study in Rule Extraction. Int. J. Neural Syst. 8 (4) (1997)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jude W. Shavlik