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Lyle H. Ungar: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Gregory Z. Grudic, Lyle H. Ungar
    Localizing Search in Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2000, pp:590-595 [Conf]
  2. David C. Parkes, Lyle H. Ungar
    Iterative Combinatorial Auctions: Theory and Practice. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2000, pp:74-81 [Conf]
  3. David C. Parkes, Lyle H. Ungar
    Preventing Strategic Manipulation in Iterative Auctions: Proxy Agents and Price-Adjustment. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2000, pp:82-89 [Conf]
  4. Alexandrin Popescul, Gary William Flake, Steve Lawrence, Lyle H. Ungar, C. Lee Giles
    Clustering and Identifying Temporal Trends in Document Databases. [Citation Graph (0, 0)][DBLP]
    ADL, 2000, pp:173-182 [Conf]
  5. David C. Parkes, Lyle H. Ungar
    An auction-based method for decentralized train scheduling. [Citation Graph (0, 0)][DBLP]
    Agents, 2001, pp:43-50 [Conf]
  6. David C. Parkes, Lyle H. Ungar, Dean P. Foster
    Accounting for Cognitive Costs in On-Line Auction Design. [Citation Graph (0, 0)][DBLP]
    AMET, 1998, pp:25-40 [Conf]
  7. Alexandrin Popescul, Lyle H. Ungar, Steve Lawrence, David M. Pennock
    Statistical Relational Learning for Document Mining. [Citation Graph (0, 0)][DBLP]
    ICDM, 2003, pp:275-282 [Conf]
  8. Panos M. Markopoulos, Ravi Aron, Lyle H. Ungar
    Dual Pricing in Electronic Markets. [Citation Graph (0, 0)][DBLP]
    ICIS, 2003, pp:485-496 [Conf]
  9. Panos M. Markopoulos, Ravi Aron, Lyle H. Ungar
    Is Online Product Information Availability Driven by Quality or Differentiation? [Citation Graph (0, 0)][DBLP]
    ICIS, 2005, pp:- [Conf]
  10. Gregory Z. Grudic, Lyle H. Ungar
    Localizing Policy Gradient Estimates to Action Transition. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:343-350 [Conf]
  11. Dmitry Pavlov, Alexandrin Popescul, David M. Pennock, Lyle H. Ungar
    Mixtures of Conditional Maximum Entropy Models. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:584-591 [Conf]
  12. Marcos Salganicoff, Lyle H. Ungar
    Active Exploration and Learning in real-Valued Spaces using Multi-Armed Bandit Allocation Indices. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:480-487 [Conf]
  13. Dale Schuurmans, Lyle H. Ungar, Dean P. Foster
    Characterizing the generalization performance of model selection strategies. [Citation Graph (0, 0)][DBLP]
    ICML, 1997, pp:340-348 [Conf]
  14. Gregory Z. Grudic, Lyle H. Ungar
    Exploiting Multiple Secondary Reinforcers in Policy Gradient Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2001, pp:965-972 [Conf]
  15. Seung-Taek Park, Alexy Khrabrov, David M. Pennock, Steve Lawrence, C. Lee Giles, Lyle H. Ungar
    Static and Dynamic Analysis of the Internet's Susceptibility to Faults and Attacks. [Citation Graph (0, 0)][DBLP]
    INFOCOM, 2003, pp:- [Conf]
  16. Eugen C. Buehler, Lyle H. Ungar
    Maximum entropy methods for biological sequence modeling. [Citation Graph (0, 0)][DBLP]
    BIOKDD, 2001, pp:60-64 [Conf]
  17. Andrew McCallum, Kamal Nigam, Lyle H. Ungar
    Efficient clustering of high-dimensional data sets with application to reference matching. [Citation Graph (0, 0)][DBLP]
    KDD, 2000, pp:169-178 [Conf]
  18. Alexandrin Popescul, Lyle H. Ungar
    Cluster-based concept invention for statistical relational learning. [Citation Graph (0, 0)][DBLP]
    KDD, 2004, pp:665-670 [Conf]
  19. Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H. Ungar
    Streaming feature selection using alpha-investing. [Citation Graph (0, 0)][DBLP]
    KDD, 2005, pp:384-393 [Conf]
  20. Jinying Chen, Andrew I. Schein, Lyle H. Ungar, Martha Palmer
    An Empirical Study of the Behavior of Active Learning for Word Sense Disambiguation. [Citation Graph (0, 0)][DBLP]
    HLT-NAACL, 2006, pp:- [Conf]
  21. Gregory Z. Grudic, Lyle H. Ungar
    Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:1515-1522 [Conf]
  22. Panos M. Markopoulos, Lyle H. Ungar
    Pricing price information in e-commerce. [Citation Graph (0, 0)][DBLP]
    ACM Conference on Electronic Commerce, 2001, pp:260-263 [Conf]
  23. Andrew I. Schein, Alexandrin Popescul, Lyle H. Ungar, David M. Pennock
    Methods and metrics for cold-start recommendations. [Citation Graph (0, 0)][DBLP]
    SIGIR, 2002, pp:253-260 [Conf]
  24. Alexandrin Popescul, Lyle H. Ungar, David M. Pennock, Steve Lawrence
    Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:437-444 [Conf]
  25. Eugen C. Buehler, Jeffrey R. Sachs, Kui Shao, Ansuman Bagchi, Lyle H. Ungar
    The CRASSS plug-in for integrating annotation data with hierarchical clustering results. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2004, v:20, n:17, pp:3266-3269 [Journal]
  26. Ted Sandler, Andrew I. Schein, Lyle H. Ungar
    Automatic term list generation for entity tagging. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2006, v:22, n:6, pp:651-657 [Journal]
  27. Andrew I. Schein, Alexandrin Popescul, Lyle H. Ungar, David M. Pennock
    CROC: A New Evaluation Criterion for Recommender Systems. [Citation Graph (0, 0)][DBLP]
    Electronic Commerce Research, 2005, v:5, n:1, pp:51-74 [Journal]
  28. Jonathan M. Vinson, Stephen D. Grantham, Lyle H. Ungar
    Automatic Rebuilding of Qualitative Models for Diagnosis. [Citation Graph (0, 0)][DBLP]
    IEEE Expert, 1992, v:7, n:4, pp:23-30 [Journal]
  29. Phillip P. Le, Amit Bahl, Lyle H. Ungar
    Using prior knowledge to improve genetic network reconstruction from microarray data. [Citation Graph (0, 0)][DBLP]
    In Silico Biology, 2004, v:4, n:, pp:- [Journal]
  30. Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H. Ungar
    Streamwise Feature Selection. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1861-1885 [Journal]
  31. Marcos Salganicoff, Lyle H. Ungar, Ruzena Bajcsy
    Active Learning for Vision-Based Robot Grasping. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1996, v:23, n:2-3, pp:251-278 [Journal]
  32. Andrew I. Schein, Lyle H. Ungar
    Active learning for logistic regression: an evaluation. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2007, v:68, n:3, pp:235-265 [Journal]

  33. Using sequence classification for filtering web pages. [Citation Graph (, )][DBLP]


  34. Web-scale named entity recognition. [Citation Graph (, )][DBLP]


  35. Extracting Product Comparisons from Discussion Boards. [Citation Graph (, )][DBLP]


  36. Finding Cohesive Clusters for Analyzing Knowledge Communities. [Citation Graph (, )][DBLP]


  37. Efficient Feature Selection in the Presence of Multiple Feature Classes. [Citation Graph (, )][DBLP]


  38. Resolving Identity Uncertainty with Learned Random Walks. [Citation Graph (, )][DBLP]


  39. Efficient Clustering of Web-Derived Data Sets. [Citation Graph (, )][DBLP]


  40. An Approach to Web-Scale Named-Entity Disambiguation. [Citation Graph (, )][DBLP]


  41. Regularized Learning with Networks of Features. [Citation Graph (, )][DBLP]


  42. Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC). [Citation Graph (, )][DBLP]


  43. Protein-Protein Interaction Network Alignment by Quantitative Simulation. [Citation Graph (, )][DBLP]


  44. Multiway Clustering for Creating Biomedical Term Sets. [Citation Graph (, )][DBLP]


  45. A predictive model for identifying mini-regulatory modules in the mouse genome. [Citation Graph (, )][DBLP]


  46. Transfer Learning Using Feature Selection [Citation Graph (, )][DBLP]


  47. Information markets for product attributes: A game theoretic, dual pricing mechanism. [Citation Graph (, )][DBLP]


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