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Note: Links lead to the DBLP on the Web. Shivakumar Vaithyanathan David Gondek , Shivakumar Vaithyanathan, Ashutosh Garg : Clustering with Model-level Constraints. SDM 2005 Douglas Burdick , Prasad Deshpande , T. S. Jayram , Raghu Ramakrishnan , Shivakumar Vaithyanathan: OLAP Over Uncertain and Imprecise Data. VLDB 2005 : 970-981 Philip Beineke , Trevor Hastie , Shivakumar Vaithyanathan: The Sentimental Factor: Improving Review Classification Via Human-Provided Information. ACL 2004 : 263-270 Ashutosh Garg , T. S. Jayram , Shivakumar Vaithyanathan, Huaiyu Zhu : Generalized Opinion Pooling. AMAI 2004 Huaiyu Zhu , Shivakumar Vaithyanathan, Mahesh V. Joshi : Topic Learning from Few Examples. PKDD 2003 : 483-494 Bo Pang , Lillian Lee , Shivakumar Vaithyanathan: Thumbs up? Sentiment Classification using Machine Learning Techniques CoRR cs.CL/0205070 : (2002) Alex Cozzi , Myron Flickner , Jianchang Mao , Shivakumar Vaithyanathan: A Comparison of Classifiers for Real-Time Eye Detection. ICANN 2001 : 993-999 Shivakumar Vaithyanathan, Byron Dom : Hierarchical Unsupervised Learning. ICML 2000 : 1039-1046 Shivakumar Vaithyanathan, Jianchang Mao , Byron Dom : Hierarchical Bayes for Text Classification. PRICAI Workshop on Text and Web Mining 2000 : 36-43 Shivakumar Vaithyanathan, Byron Dom : Model-Based Hierarchical Clustering. UAI 2000 : 599-608 Shivakumar Vaithyanathan, Byron Dom : Model Selection in Unsupervised Learning with Applications To Document Clustering. ICML 1999 : 433-443 Shivakumar Vaithyanathan, Byron Dom : Generalized Model Selection for Unsupervised Learning in High Dimensions. NIPS 1999 : 970-976 Shivakumar Vaithyanathan: Introduction: Data Mining on the Internet. Artif. Intell. Rev. 13 (5-6): 343-344 (1999) Peter G. Anick , Shivakumar Vaithyanathan: Exploiting Clustering and Phrases for Context-based Information Retrieval. SIGIR 1997 : 314-323 Shivakumar Vaithyanathan, James P. Ignizio : A stochastic neural network for resource constrained scheduling. Computers & OR 19 (3-4): 241-254 (1992) 1 [ 2 ] 2 [ 13 ] 3 [ 14 ] 4 [ 9 ] 5 [ 14 ] 6 [ 4 ] [ 5 ] [ 6 ] [ 7 ] [ 8 ] 7 [ 9 ] 8 [ 12 ] [ 15 ] 9 [ 15 ] 10 [ 13 ] 11 [ 1 ] 12 [ 12 ] [ 14 ] 13 [ 11 ] 14 [ 10 ] 15 [ 7 ] [ 9 ] 16 [ 10 ] 17 [ 14 ] 18 [ 11 ] [ 12 ]  ©2006 Association for Computing Machinery |
