Jude W. Shavlik

According to our database1, Jude W. Shavlik authored at least 143 papers between 1985 and 2016.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2016
Learning Relational Dependency Networks for Relation Extraction.
Proceedings of the Inductive Logic Programming - 26th International Conference, 2016

2015
Gradient-based boosting for statistical relational learning: the Markov logic network and missing data cases.
Machine Learning, 2015

TAC KBP 2015 : English Slot Filling Track Relational Learning with Expert Advice.
Proceedings of the 2015 Text Analysis Conference, 2015

Anomaly Detection in Text: The Value of Domain Knowledge.
Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, 2015

2014
Boosted Statistical Relational Learners - From Benchmarks to Data-Driven Medicine
Springer Briefs in Computer Science, Springer, ISBN: 978-3-319-13644-8, 2014

Corleone: hands-off crowdsourcing for entity matching.
Proceedings of the International Conference on Management of Data, 2014

Detecting Semantic Uncertainty by Learning Hedge Cues in Sentences Using an HMM.
Proceedings of Workshop on Semantic Matching in Information Retrieval co-located with the 37th international ACM SIGIR conference on research and development in information retrieval, 2014

Support Vector Machines for Differential Prediction.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge.
Proceedings of the Inductive Logic Programming - 24th International Conference, 2014

Classification from One Class of Examples for Relational Domains.
Proceedings of the Statistical Relational Artificial Intelligence, 2014

Relational One-Class Classification: A Non-Parametric Approach.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Bootstrapping Knowledge Base Acceleration.
Proceedings of The Twenty-Second Text REtrieval Conference, 2013

Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Uplift Modeling with ROC: An SRL Case Study.
Proceedings of the Late Breaking Papers of the 23rd International Conference on Inductive Logic Programming, Rio de Janeiro, Brazil, August 28th - to, 2013

Guiding Autonomous Agents to Better Behaviors through Human Advice.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Using machine learning to identify benign cases with non-definitive biopsy.
Proceedings of the IEEE 15th International Conference on e-Health Networking, 2013

Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms.
Proceedings of the AMIA 2013, 2013

Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text.
Proceedings of the Statistical Relational Artificial Intelligence, 2013

2012
Gradient-based boosting for statistical relational learning: The relational dependency network case.
Machine Learning, 2012

Elementary: Large-Scale Knowledge-Base Construction via Machine Learning and Statistical Inference.
Int. J. Semantic Web Inf. Syst., 2012

DeepDive: Web-scale Knowledge-base Construction using Statistical Learning and Inference.
Proceedings of the Second International Workshop on Searching and Integrating New Web Data Sources, 2012

Mirror Descent for Metric Learning: A Unified Approach.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Scaling Inference for Markov Logic via Dual Decomposition.
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Big Data versus the Crowd: Looking for Relationships in All the Right Places.
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, July 8-14, 2012, Jeju Island, Korea, 2012

Invited Talks.
Proceedings of the Discovery Informatics: The Role of AI Research in Innovating Scientific Processes, 2012

2011
Predictive Models in Personalized Medicine: Neural Information Processing Systems (NIPS), 2010 workshop report.
SIGHIT Record, 2011

Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS.
PVLDB, 2011

Advice Refinement in Knowledge-Based SVMs.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Integrating knowledge capture and supervised learning through a human-computer interface.
Proceedings of the 6th International Conference on Knowledge Capture (K-CAP 2011), 2011

Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach.
Proceedings of the IJCAI 2011, 2011

Learning Markov Logic Networks via Functional Gradient Boosting.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Probabilistic ensembles for improved inference in protein-structure determination.
Proceedings of the ACM International Conference on Bioinformatics, 2011

2010
Transfer Learning via Advice Taking.
Proceedings of the Advances in Machine Learning I: Dedicated to the Memory of Professor Ryszard S. Michalski, 2010

Validation of Results from Knowledge Discovery: Mass Density as a Predictor of Breast Cancer.
J. Digital Imaging, 2010

Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Online Knowledge-Based Support Vector Machines.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge.
Proceedings of the Inductive Logic Programming - 20th International Conference, 2010

Uncovering age-specific invasive and DCIS breast cancer rules using inductive logic programming.
Proceedings of the ACM International Health Informatics Symposium, 2010

Multi-Agent Inverse Reinforcement Learning.
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Guiding belief propagation using domain knowledge for protein-structure determination.
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology, 2010

Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.
Proceedings of the Statistical Relational Artificial Intelligence, 2010

2009
Bellwether analysis: Searching for cost-effective query-defined predictors in large databases.
TKDD, 2009

Spherical-harmonic decomposition for molecular recognition in electron-density maps.
IJDMB, 2009

Policy Transfer via Markov Logic Networks.
Proceedings of the Inductive Logic Programming, 19th International Conference, 2009

Boosting First-Order Clauses for Large, Skewed Data Sets.
Proceedings of the Inductive Logic Programming, 19th International Conference, 2009

Speeding Up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network.
Proceedings of the IJCAI 2009, 2009

Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule.
Proceedings of the International Conference on Machine Learning and Applications, 2009

Information Extraction for Clinical Data Mining: A Mammography Case Study.
Proceedings of the ICDM Workshops 2009, 2009

2008
Rule Extraction for Transfer Learning.
Proceedings of the Rule Extraction from Support Vector Machines, 2008

Guest editors' introduction: special issue on inductive logic programming (ILP-2007).
Machine Learning, 2008

Advice Taking and Transfer Learning: Naturally Inspired Extensions to Reinforcement Learning.
Proceedings of the Naturally-Inspired Artificial Intelligence, 2008

2007
Creating protein models from electron-density maps using particle-filtering methods.
Bioinformatics, 2007

Building Relational World Models for Reinforcement Learning.
Proceedings of the Inductive Logic Programming, 17th International Conference, 2007

Relational Macros for Transfer in Reinforcement Learning.
Proceedings of the Inductive Logic Programming, 17th International Conference, 2007

Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming.
Proceedings of the Inductive Logic Programming, 17th International Conference, 2007

Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates.
Proceedings of the Inductive Logic Programming, 17th International Conference, 2007

Improved Methods for Template-Matching in Electron-Density Maps Using Spherical Harmonics.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2007

Refining Rules Incorporated into Knowledge-Based Support Vector Learners Via Successive Linear Programming.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Gleaner: Creating ensembles of first-order clauses to improve recall-precision curves.
Machine Learning, 2006

Bellwether Analysis: Predicting Global Aggregates from Local Regions.
Proceedings of the 32nd International Conference on Very Large Data Bases, 2006

A probabilistic approach to protein backbone tracing in electron density maps.
Proceedings of the Proceedings 14th International Conference on Intelligent Systems for Molecular Biology 2006, 2006

Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition.
Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006

Skill Acquisition Via Transfer Learning and Advice Taking.
Proceedings of the Machine Learning: ECML 2006, 2006

A Simple and Effective Method for Incorporating Advice into Kernel Methods.
Proceedings of the Proceedings, 2006

2005
Knowledge transfer via advice taking.
Proceedings of the 3rd International Conference on Knowledge Capture (K-CAP 2005), 2005

A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment.
Proceedings of the Inductive Logic Programming, 15th International Conference, 2005

View Learning for Statistical Relational Learning: With an Application to Mammography.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another.
Proceedings of the Machine Learning: ECML 2005, 2005

Giving Advice about Preferred Actions to Reinforcement Learners Via Knowledge-Based Kernel Regression.
Proceedings of the Proceedings, 2005

2004
Knowledge-Based Kernel Approximation.
Journal of Machine Learning Research, 2004

Using Machine Learning to Design and Interpret Gene-Expression Microarrays.
AI Magazine, 2004

Pictorial Structures for Molecular Modeling: Interpreting Density Maps.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Scaling Up ILP: Experiences with Extracting Relations from Biomedical Text.
Proceedings of the Inductive Logic Programming, 14th International Conference, 2004

Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction.
Proceedings of the Inductive Logic Programming, 14th International Conference, 2004

Learning an Approximation to Inductive Logic Programming Clause Evaluation.
Proceedings of the Inductive Logic Programming, 14th International Conference, 2004

A Self-Tuning Method for One-Chip SNP Identification.
Proceedings of the 3rd International IEEE Computer Society Computational Systems Bioinformatics Conference, 2004

2003
A System for Building Intelligent Agents that Learn to Retrieve and Extract Information.
User Model. User-Adapt. Interact., 2003

A Bayesian Network Approach to Operon Prediction.
Bioinformatics, 2003

Applying Theory Revision to the Design of Distributed Databases.
Proceedings of the Inductive Logic Programming: 13th International Conference, 2003

Toward Automatic Management of Embarrassingly Parallel Applications.
Proceedings of the Euro-Par 2003. Parallel Processing, 2003

Knowledge-Based Nonlinear Kernel Classifiers.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
Report on the First International Conference on Knowledge Capture (K-CAP).
AI Magazine, 2002

Knowledge-Based Support Vector Machine Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Interpreting Microarray Expression Data Using Text Annotating the Genes.
Proceedings of the 6th Joint Conference on Information Science, 2002

Evaluating machine learning approaches for aiding probe selection for gene-expression arrays.
Proceedings of the Tenth International Conference on Intelligent Systems for Molecular Biology, 2002

An Empirical Evaluation of Bagging in Inductive Logic Programming.
Proceedings of the Inductive Logic Programming, 12th International Conference, 2002

2001
A Theory-Refinement Approach to Information Extraction.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

2000
Learning users' interests by unobtrusively observing their normal behavior.
Proceedings of the 5th International Conference on Intelligent User Interfaces, 2000

A Probabilistic Learning Approach to Whole-Genome Operon Prediction.
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology, 2000

Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

1999
Neural network input representations that produce accurate consensus sequences from DNA fragment assemblies.
Bioinformatics, 1999

An Instructable, Adaptive Interface for Discovering and Monitoring Information on the World-Wide Web.
Proceedings of the 4th International Conference on Intelligent User Interfaces, 1999

Bridging Science and Applications (Panel).
Proceedings of the 4th International Conference on Intelligent User Interfaces, 1999

1997
Connectionist Theory Refinement: Genetically Searching the Space of Network Topologies.
J. Artif. Intell. Res., 1997

Understanding Time-Series Networks: A Case Study in Rule Extraction.
Int. J. Neural Syst., 1997

Using neural networks for data mining.
Future Generation Comp. Syst., 1997

Increasing Consensus Accuracy in DNA Fragment Assemblies by Incorporating Fluorescent Trace Representations.
Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology, 1997

1996
Creating Advice-Taking Reinforcement Learners.
Machine Learning, 1996

Actively Searching for an Effective Neural Network Ensemble.
Connect. Sci., 1996

Growing Simpler Decision Trees to Facilitate Knowledge Discovery.
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 1996

Improving the Quality of Automatic DNA Sequence Assembly Using Fluorescent Trace-Data Classifications.
Proceedings of the Fourth International Conference on Intelligent Systems for Molecular Biology, 1996

1995
Introduction.
Machine Learning, 1995

Dynamically adding symbolically meaningful nodes to knowledge-based neural networks.
Knowl.-Based Syst., 1995

Generating Accurate and Diverse Members of a Neural-Network Ensemble.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Extracting Tree-Structured Representations of Trained Networks.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Rapid Quality Estimation of Neural Network Input Representations.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Combining the Predictions of Multiple Classifiers: Using Competitive Learning to Initialize Neural Networks.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

1994
Combining Symbolic and Neural Learning.
Machine Learning, 1994

Machine Learning Approaches to Gene Recognition.
IEEE Expert, 1994

The First International Conference on Intelligent Systems for Molecular Biology.
AI Magazine, 1994

Knowledge-Based Artificial Neural Networks.
Artif. Intell., 1994

Using Genetic Search to Refine Knowledge-based Neural Networks.
Proceedings of the Machine Learning, 1994

Using Sampling and Queries to Extract Rules from Trained Neural Networks.
Proceedings of the Machine Learning, 1994

Incorporating Advice into Agents that Learn from Reinforcements.
Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, WA, USA, July 31, 1994

1993
Extracting Refined Rules from Knowledge-Based Neural Networks.
Machine Learning, 1993

Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools.
Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology, 1993

Heuristically Expanding Knowledge-Based Neural Networks.
Proceedings of the 13th International Joint Conference on Artificial Intelligence. Chambéry, France, August 28, 1993

Learning to Represent Codons: A Challenge Problem for Constructive Induction.
Proceedings of the 13th International Joint Conference on Artificial Intelligence. Chambéry, France, August 28, 1993

Learning Symbolic Rules Using Artificial Neural Networks.
Proceedings of the Machine Learning, 1993

1992
Refining PID Controllers Using Neural Networks.
Neural Computation, 1992

Visualizing Learning and Computation in Artificial Neural Networks.
International Journal on Artificial Intelligence Tools, 1992

Using Symbolic Learning to Improve Knowledge-Based Neural Networks.
Proceedings of the 10th National Conference on Artificial Intelligence, 1992

Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein Folding.
Proceedings of the 10th National Conference on Artificial Intelligence, 1992

1991
Symbolic and Neural Learning Algorithms: An Experimental Comparison.
Machine Learning, 1991

Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

Refined PID Controllers Using Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

Constructive Induction in Knowledge-Based Neural Networks.
Proceedings of the Eighth International Workshop (ML91), 1991

Refining Domain Theories Expressed as Finite-State Automata.
Proceedings of the Eighth International Workshop (ML91), 1991

1990
Acquiring Recursive and Iterative Concepts with Explanation-Based Learning.
Machine Learning, 1990

Learning in Mathematically-Based Domains: Understanding and Generalizing Obstacle Cancellations.
Artif. Intell., 1990

Training Knowledge-Based Neural Networks to Recognize Genes.
Proceedings of the Advances in Neural Information Processing Systems 3, 1990

Refinement ofApproximate Domain Theories by Knowledge-Based Neural Networks.
Proceedings of the 8th National Conference on Artificial Intelligence. Boston, Massachusetts, USA, July 29, 1990

1989
Acquiring Recursive Concepts with Explanation-Based Learning.
Proceedings of the 11th International Joint Conference on Artificial Intelligence. Detroit, 1989

An Experimental Comparison of Symbolic and Connectionist Learning Algorithms.
Proceedings of the 11th International Joint Conference on Artificial Intelligence. Detroit, 1989

Combining Explanation-Based Learning and Artificial Neural Networks.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

An Empirical Analysis of EBL Approaches for Learning Plan Schemata.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

Enriching Vocabularies by Generalizing Explanation Structures.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

Processing Issues in Comparisons of Symbolic and Connectionist Learning Systems.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

1987
An Explanation-based Approach to Generalizing Number.
Proceedings of the 10th International Joint Conference on Artificial Intelligence. Milan, 1987

BAGGER: An EBL System that Extends and Generalizes Explanations.
Proceedings of the 6th National Conference on Artificial Intelligence. Seattle, 1987

1986
Computer understanding and generalization of symbolic mathematical calculations: a case study in physics problem solving.
Proceedings of the SYMSAC 1986, 1986

1985
Learning about Momentum Conservation.
Proceedings of the 9th International Joint Conference on Artificial Intelligence. Los Angeles, 1985


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