2008 |
40 | EE | Casey Whitelaw,
Alex Kehlenbeck,
Nemanja Petrovic,
Lyle H. Ungar:
Web-scale named entity recognition.
CIKM 2008: 123-132 |
39 | EE | Binyamin Rosenfeld,
Ronen Feldman,
Lyle H. Ungar:
Using sequence classification for filtering web pages.
CIKM 2008: 1355-1356 |
38 | EE | Paramveer S. Dhillon,
Dean Foster,
Lyle H. Ungar:
Efficient Feature Selection in the Presence of Multiple Feature Classes.
ICDM 2008: 779-784 |
37 | EE | Ted Sandler,
John Blitzer,
Partha Pratim Talukdar,
Lyle H. Ungar:
Regularized Learning with Networks of Features.
NIPS 2008: 1401-1408 |
36 | EE | Ravi Aron,
Lyle H. Ungar,
Annapurna Valluri:
A model of market power and efficiency in private electronic exchanges.
European Journal of Operational Research 187(3): 922-942 (2008) |
2007 |
35 | EE | Vasileios Kandylas,
S. Phineas Upham,
Lyle H. Ungar:
Finding Cohesive Clusters for Analyzing Knowledge Communities.
ICDM 2007: 203-212 |
34 | EE | Ronen Feldman,
Moshe Fresko,
Jacob Goldenberg,
Oded Netzer,
Lyle H. Ungar:
Extracting Product Comparisons from Discussion Boards.
ICDM 2007: 469-474 |
33 | EE | Andrew I. Schein,
Lyle H. Ungar:
Active learning for logistic regression: an evaluation.
Machine Learning 68(3): 235-265 (2007) |
2006 |
32 | | Tina Eliassi-Rad,
Lyle H. Ungar,
Mark Craven,
Dimitrios Gunopulos:
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, August 20-23, 2006
ACM 2006 |
31 | EE | Jinying Chen,
Andrew I. Schein,
Lyle H. Ungar,
Martha Palmer:
An Empirical Study of the Behavior of Active Learning for Word Sense Disambiguation.
HLT-NAACL 2006 |
30 | EE | Ted Sandler,
Andrew I. Schein,
Lyle H. Ungar:
Automatic term list generation for entity tagging.
Bioinformatics 22(6): 651-657 (2006) |
29 | EE | Jing Zhou,
Dean P. Foster,
Robert A. Stine,
Lyle H. Ungar:
Streamwise Feature Selection.
Journal of Machine Learning Research 7: 1861-1885 (2006) |
2005 |
28 | | Panos M. Markopoulos,
Ravi Aron,
Lyle H. Ungar:
Is Online Product Information Availability Driven by Quality or Differentiation?
ICIS 2005 |
27 | EE | Jing Zhou,
Dean P. Foster,
Robert A. Stine,
Lyle H. Ungar:
Streaming feature selection using alpha-investing.
KDD 2005: 384-393 |
26 | EE | Andrew I. Schein,
Alexandrin Popescul,
Lyle H. Ungar,
David M. Pennock:
CROC: A New Evaluation Criterion for Recommender Systems.
Electronic Commerce Research 5(1): 51-74 (2005) |
2004 |
25 | EE | Alexandrin Popescul,
Lyle H. Ungar:
Cluster-based concept invention for statistical relational learning.
KDD 2004: 665-670 |
24 | EE | 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.
Bioinformatics 20(17): 3266-3269 (2004) |
23 | EE | Phillip P. Le,
Amit Bahl,
Lyle H. Ungar:
Using prior knowledge to improve genetic network reconstruction from microarray data.
In Silico Biology 4: (2004) |
2003 |
22 | EE | Alexandrin Popescul,
Lyle H. Ungar,
Steve Lawrence,
David M. Pennock:
Statistical Relational Learning for Document Mining.
ICDM 2003: 275-282 |
21 | | Panos M. Markopoulos,
Ravi Aron,
Lyle H. Ungar:
Dual Pricing in Electronic Markets.
ICIS 2003: 485-496 |
20 | | Dmitry Pavlov,
Alexandrin Popescul,
David M. Pennock,
Lyle H. Ungar:
Mixtures of Conditional Maximum Entropy Models.
ICML 2003: 584-591 |
19 | EE | 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.
INFOCOM 2003 |
2002 |
18 | EE | Andrew I. Schein,
Alexandrin Popescul,
Lyle H. Ungar,
David M. Pennock:
Methods and metrics for cold-start recommendations.
SIGIR 2002: 253-260 |
2001 |
17 | EE | Panos M. Markopoulos,
Lyle H. Ungar:
Pricing price information in e-commerce.
ACM Conference on Electronic Commerce 2001: 260-263 |
16 | EE | David C. Parkes,
Lyle H. Ungar:
An auction-based method for decentralized train scheduling.
Agents 2001: 43-50 |
15 | EE | Eugen C. Buehler,
Lyle H. Ungar:
Maximum entropy methods for biological sequence modeling.
BIOKDD 2001: 60-64 |
14 | | Gregory Z. Grudic,
Lyle H. Ungar:
Exploiting Multiple Secondary Reinforcers in Policy Gradient Reinforcement Learning.
IJCAI 2001: 965-972 |
13 | EE | Gregory Z. Grudic,
Lyle H. Ungar:
Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning.
NIPS 2001: 1515-1522 |
12 | EE | Alexandrin Popescul,
Lyle H. Ungar,
David M. Pennock,
Steve Lawrence:
Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments.
UAI 2001: 437-444 |
2000 |
11 | | Gregory Z. Grudic,
Lyle H. Ungar:
Localizing Search in Reinforcement Learning.
AAAI/IAAI 2000: 590-595 |
10 | | David C. Parkes,
Lyle H. Ungar:
Iterative Combinatorial Auctions: Theory and Practice.
AAAI/IAAI 2000: 74-81 |
9 | | David C. Parkes,
Lyle H. Ungar:
Preventing Strategic Manipulation in Iterative Auctions: Proxy Agents and Price-Adjustment.
AAAI/IAAI 2000: 82-89 |
8 | EE | Alexandrin Popescul,
Gary William Flake,
Steve Lawrence,
Lyle H. Ungar,
C. Lee Giles:
Clustering and Identifying Temporal Trends in Document Databases.
ADL 2000: 173-182 |
7 | | Gregory Z. Grudic,
Lyle H. Ungar:
Localizing Policy Gradient Estimates to Action Transition.
ICML 2000: 343-350 |
6 | EE | Andrew McCallum,
Kamal Nigam,
Lyle H. Ungar:
Efficient clustering of high-dimensional data sets with application to reference matching.
KDD 2000: 169-178 |
1998 |
5 | EE | David C. Parkes,
Lyle H. Ungar,
Dean P. Foster:
Accounting for Cognitive Costs in On-Line Auction Design.
AMET 1998: 25-40 |
1997 |
4 | | Dale Schuurmans,
Lyle H. Ungar,
Dean P. Foster:
Characterizing the generalization performance of model selection strategies.
ICML 1997: 340-348 |
1996 |
3 | | Marcos Salganicoff,
Lyle H. Ungar,
Ruzena Bajcsy:
Active Learning for Vision-Based Robot Grasping.
Machine Learning 23(2-3): 251-278 (1996) |
1995 |
2 | | Marcos Salganicoff,
Lyle H. Ungar:
Active Exploration and Learning in real-Valued Spaces using Multi-Armed Bandit Allocation Indices.
ICML 1995: 480-487 |
1992 |
1 | EE | Jonathan M. Vinson,
Stephen D. Grantham,
Lyle H. Ungar:
Automatic Rebuilding of Qualitative Models for Diagnosis.
IEEE Expert 7(4): 23-30 (1992) |