- Streaming Feature Selection using IIC Lyle H. Ungar and Jing Zhou
- Maximum Entropy Methods for Biological Sequence Eugen C. Buehler
- Using Policy Gradient Reinforcement Learning on Autonomous Robot Controllers
- Lyle Ungar, University of Pennsylvania Information ExtractionInformation Extraction
- COORDINATING LOCALLY CONSTRAINED AGENTS USING AUGMENTED RINALDO A. JOSE, PATRICK T. HARKER, AND LYLE H. UNGAR
- A Formal Statistical Approach to Collaborative Filtering Lyle H. Ungar and Dean P. Foster
- Clustering and Identifying Temporal Trends in Document Databases
- Characterizing the generalization performance of model selection strategies
- Radial Basis Functions for Process Control Lyle H. Ungar Tom Johnson Richard D. De Veaux
- Selected Neural Networks Bibliography As there are dozens of books and tens of thousands of articles on neural networks, this does
- A Brief Introduction to Neural Networks Richard D. De Veaux Lyle H. Ungar
- In Proceedings of IEEE International Conference on Data Mining, ICDM2003. Statistical Relational Learning for Document Mining
- Characterizing the generalization performance of model selection strategies
- In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI-2001), to appear, Morgan Kaufmann, San Francisco, 2001.
- Clustering and Identifying Temporal Trends in Document Databases
- Clustering Methods for Collaborative Filtering Lyle H. Ungar and Dean P. Foster
- A Formal Statistical Approach to Collaborative Filtering Lyle H. Ungar and Dean P. Foster
- In Multi-Relational Data Mining Workshop at KDD-2003. Structural Logistic Regression for Link Analysis
- In Proc. of the Workshop on Learning Statistical Models from Relational Data at IJCAI-2003. Statistical Relational Learning for Link Prediction
- A-Optimality for Active Learning of Logistic Regression Classifiers Andrew I. Schein and Lyle H. Ungar
- EMRBF: A Statistical Basis for Using Radial Basis Functions for Process Control
- Clusterbased Concept Invention for Statistical Relational Learning
- A Hybrid Neural Network-First Principles Approach to Process Modeling
- In MultiRelational Data Mining Workshop at KDD2003. Structural Logistic Regression for Link Analysis
- Dynamic Feature Generation for Relational Learning Alexandrin Popescul and Lyle H. Ungar
- The Tragedy of the Commons: Pricing Social Welfare in Multiagent Systems
- Estimating Prediction Intervals for Arti cial Neural Lyle H. Ungar Richard D. De Veaux Evelyn Rosengarten
- Clustering Methods for Collaborative Filtering Lyle H. Ungar and Dean P. Foster
- Draft Prediction Intervals for Neural Networks via Nonlinear Regression
- AUCTIONDRIVEN COORDINATION FOR PLANTWIDE OPTIMIZATION
- Cluster-based Concept Invention for Statistical Relational Learning
- In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI2001), to appear, Morgan Kaufmann, San Francisco, 2001.
- Maximum Entropy Methods for Biological Sequence Eugen C. Buehler \Lambda
- Streaming Feature Selection using Alpha-investing Electrical and Systems Engineering
- Integrated Annotation for Biomedical Information Extraction Seth Kulick and Ann Bies and Mark Liberman and Mark Mandel
- Auctions and Optimization: Methods for Closing the Gap Caused by NonConvexities in Preferences
- In MultiRelational Data Mining Workshop at KDD2002. Towards Structural Logistic Regression
- In Proc. of the Workshop on Learning Statistical Models from Relational Data at IJCAI2003. Statistical Relational Learning for Link Prediction
- Estimating Monotonic Functions and Their Herbert Kay
- PennAspect: Two-Way Aspect Model Implementation Andrew I. Schein y , Alexandrin Popescul, Lyle H. Ungar
- Appeared in Proceedings of the 25'th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2002), pp. 253260. Tampere, Finland. August, 2002.
- Selected references for Text Mining Named Entity Extraction
- String Edit Analysis for Merging Databases J. Joanne Zhu and Lyle H. Ungar
- A NEURAL NETWORK ARCHITECTURE THAT COMPUTES ITS OWN RELIABILITY
- Estimating Prediction Intervals for Artificial Neural Lyle H. Ungar Richard D. De Veaux Evelyn Rosengarten
- Multicollinearity: A tale of two nonparametric regressions
- MGMT 560: Management of Technology Professor Lyle Ungar
- Workshop on Learning Statistical Models from Relational Data, IJCAI2003 Statistical Relational Learning at U Penn
- Learning Object Permanence by Ontological Leaps Dean Foster (foster@diskworld.wharton.upenn.edu)
- Prediction Intervals for Neural Networks via Nonlinear Regression
- Appeared in Proceedings of the 25'th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2002), pp. 253-260. Tampere, Finland. August, 2002.
