- Improving the Quality of Automatic DNA Sequence Assembly using Fluorescent Trace-Data Classifications
- Multi-Agent Inverse Reinforcement Learning Sriraam Natarajan
- View Learning for Statistical Relational Learning: With an Application to Mammography
- Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models
- EXTRACTING COMPREHENSIBLE MODELS FROM TRAINED NEURAL NETWORKS
- EMPIRICAL TESTS OF KBANN This chapter details empirical tests that explore how well Kbann works as opposed to the
- Relational Macros for Transfer in Reinforcement Learning Lisa Torrey,Jude Shavlik,Trevor Walker
- Refining Rules Incorporated into Knowledge-Based Support Vector Learners Via Successive Linear Programming
- UNIVERSITY OF WISCONSIN, MACHINE LEARNING RESEARCH GROUP WORKING PAPER 06-1, SEPTEMBER 2006 Improving the Efficiency of Belief Propagation
- Machine Learning in Structural Biology: Interpreting 3D Protein
- An Empirical Study of Machine Learning Algorithms Applied to Modeling Player Behavior in a "First Person Shooter" Video Game
- Novel Uses for Machine Learning and Other Computational Methods for the Design and Interpretation
- SYMBOLIC KNOWLEDGE AND NEURAL NETWORKS: INSERTION, REFINEMENT AND EXTRACTION
- Spherical-Harmonic Decomposition for Molecular
- Vol. 22 no. 14 2006, pages e81e89 doi:10.1093/bioinformatics/btl252BIOINFORMATICS
- Appears in the AI Magazine, Special Issue on Bioinformatics. USING MACHINE LEARNING TO DESIGN AND INTERPRET
- UNCORRECTEDPROOF Interpreting microarray expression data
- Neural Network Input Representations that Produce Accurate Consensus Sequences from DNA Fragment Assemblies
- Appears in Artificial Intelligence, volume 69 or 70. Submitted 1/92, Final pre-publication revisions 8/94
- Uncovering Age-Specific Invasive and DCIS Breast Cancer Rules Using Inductive Logic Programming
- Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule
- Policy Transfer via Markov Logic Networks Lisa Torrey and Jude Shavlik
- Learning an Approximation to Inductive Logic Programming Clause Evaluation
- Selection, Combination, and Evaluation of Effective Software Sensors for
- Applying Theory Revision to the Design of Distributed Databases
- Intelligent Web Agents that Learn to Retrieve and Extract Information
- Machine Learning Research Group Working Paper 91-2 Refining Algorithms with Knowledge-Based Neural Networks
- Appears in Proceedings of the 2009 IEEE International Conference on Data Mining Workshops Information Extraction for Clinical Data Mining
- Anytime Lifted Belief Propagation Rodrigo de Salvo Braz braz@ai.sri.com
- Appears in the Proceedings of the ICDM Workshop on Foundations and New Directions of Data Mining, November 2003 Speeding Up Relational Data Mining by Learning to
- Appears in the Working Notes of the ICML Workshop on Machine Learning in Bioinformatics, August 2003 Using Pictorial Structures to Identify Proteins
- Appears in the Proceedings of the National Science Foundation Workshop on Next Generation Data Mining, Nov. 2002, Baltimore, MD. Relational Data Mining with Inductive Logic Programming for Link Discovery
- University of Wisconsin Machine Learning Group Working Paper 06-2 Advice-based Transfer
- Probabilistic Methods for Interpreting Electron-Density Maps
- BUILDING INTELLIGENT AGENTS THAT LEARN TO RETRIEVE AND EXTRACT
- APPEARS IN THE PROCEEDINGS OF THE SIXTH IEEE CONFERENCE ON DATA MINING (ICDM), 2006 Belief Propagation in Large, Highly Connected Graphs
- Appears in Advances in Neural Information Processing Systems Vol. 17 MIT Press, Cambridge, MA, 2005
- Knowledge-Based Support Vector Machine Classifiers
- University of Wisconsin, Machine Learning Research Group Working Paper BUILDING GENOME EXPRESSION MODELS USING
- APPEARS IN THE PROCEEDINGS OF THE IEEE CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), 2007 Improved Methods for Template-Matching in Electron-Density Maps
- BUILDING INTELLIGENT AGENTS THAT LEARN TO RETRIEVE AND EXTRACT
- Appears in Machine Learning: Proceedings of the Eighth International Workshop, Birnbaum, L. and Collins, G. (eds.), Morgan Kaufmann, San Mateo, Ca., 1991
- Appears in the AAAI-04 workshop on Supervisory Control of Learning and Adaptive Systems. Guiding a Reinforcement Learner with Natural Language Advice
- Bellwether Analysis: Predicting Global Aggregates from Local Regions Bee-Chung Chen
- AN ANYTIME APPROACH TO CONNECTIONIST THEORY REFINEMENT
- An Empirical Study of Machine Learning Algorithms Applied to Modeling Player Behavior in a ``First Person Shooter'' Video Game
- Appears in the Proceedings of the 18th International Conference on Machine Learning (ICML 2001).
- Increasing Consensus Accuracy in DNA Fragment Assemblies by Incorporating Fluorescent Trace Representations
- Appears in: The Proceedings of the IEEE Conference on Computational Systems Bioinformatics (CSB 2004) A Self-Tuning Method for One-Chip SNP Identification
- ADAPTIVELY FINDING AND COMBINING FIRST-ORDER RULES FOR LARGE, SKEWED DATA SETS
- COMPUTATIONAL METHODS FOR FAST AND ACCURATE DNA FRAGMENT ASSEMBLY
- Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach
- Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models
- Boosting First-Order Clauses for Large, Skewed Data Sets
- Transferring Advice into a Connectionist
- Knowledge-Based Nonlinear Kernel Classifiers Glenn M. Fung, Olvi L. Mangasarian , and Jude W. Shavlik
- Validation of Results from Knowledge Discovery: Mass Density as a Predictor of Breast Cancer
- Appears in the Proceedings of the 2010 ACM International Conference on Bioinformatics and Computational Biology (ACM-BCB 2010), Niagara Falls, NY, USA
- LEARNING FROM STUDENTS TO IMPROVE AN INTELLIGENT TUTORING Eric Gutstein
- Presented at the Fourth International Symposium on Recent Advances in Intrusion Detection (RAID `01). Evaluating Software Sensors for Actively Profiling
- BIOINFORMATICS Accepted for publication 2007
- SPECIFYING EXAMPLES AND The rulestonetwork translator (Section 2.2) requires two sets of information from a user to
- Gradient-based Boosting for Statistical Relational Learning
- Learning to Extract Genic Interactions Using Gleaner Mark Goadrich richm@cs.wisc.edu
- PSYCHOLOGICAL MODELING USING KBANN
- Relational Reinforcement Learning via Sampling the Space of First-Order Conjunctive Features
- LEARNING FROM INSTRUCTION AND EXPERIENCE: METHODS FOR
- COMPUTATIONAL METHODS FOR FAST AND ACCURATE DNA FRAGMENT ASSEMBLY
- The Relationship Between Precision-Recall and ROC Curves Jesse Davis jdavis@cs.wisc.edu
- Speeding Up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network
- Submitted to Data Mining: Next Generation Challenges and Future Directions, H. Kargupta and A. Joshi (eds.), by AAAI/MIT Press
- Appears in the Proceedings of the 1991 DARPA Workshop on Case-Based Reasoning, Morgan-Kaufmann. Finding Genes by Case-Based Reasoning
- Appears in Proceedings of the 17th International Conference on Inductive Logic Programming (ILP). Corvallis, Oregon, USA. June, 2007.
- TECHNIQUES FOR IMPROVED PROBABILISTIC INFERENCE IN PROTEIN-STRUCTURE DETERMINATION VIA X-RAY
- Learning Markov Logic Networks via Functional Gradient Boosting Tushar Khot, Sriraam Natarajan, Kristian Kersting and Jude Shavlik
- Integrating Machine Learning and Physician Knowledge to Improve the Accuracy of Breast Biopsy
- Broadening the Applicability of Relational Learning Trevor Walker
