Ph.D. Alumni
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Adaptive Blocking: Learning to Scale Up Record Linkage 2006
Mikhail Bilenko, Beena Kamath, Raymond J. Mooney, In Proceedings of the Sixth IEEE International Conference on Data Mining (ICDM-06), pp. 87--96, Hong Kong, December 2006.
Learnable Similarity Functions and Their Application to Record Linkage and Clustering 2006
Mikhail Bilenko, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 136 pages.
Probabilistic Semi-Supervised Clustering with Constraints 2006
Sugato Basu, Mikhail Bilenko, Arindam Banerjee and Raymond J. Mooney, In Semi-Supervised Learning, O. Chapelle and B. Sch{"{o}}lkopf and A. Zien (Eds.), Cambridge, MA 2006. MIT Press.
Adaptive Product Normalization: Using Online Learning for Record Linkage in Comparison Shopping 2005
Mikhail Bilenko, Sugato Basu, and Mehran Sahami, In Proceedings of the 5th International Conference on Data Mining (ICDM-2005), pp. 58--65, Houston, TX, November 2005.
Alignments and String Similarity in Information Integration: A Random Field Approach 2005
Mikhail Bilenko and Raymond J. Mooney, In Proceedings of the 2005 Dagstuhl Seminar on Machine Learning for the Semantic Web, Dagstuhl, Germany, February 2005.
A Comparison of Inference Techniques for Semi-supervised Clustering with Hidden Markov Random Fields 2004
Mikhail Bilenko and Sugato Basu, In Proceedings of the ICML-2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL-2004), Banff, Canada, July 2004.
A Probabilistic Framework for Semi-Supervised Clustering 2004
Sugato Basu, Mikhail Bilenko, and Raymond J. Mooney, In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2004), pp. 59-68, Seattle, WA, August 2004.
Integrating Constraints and Metric Learning in Semi-Supervised Clustering 2004
Mikhail Bilenko, Sugato Basu, and Raymond J. Mooney, In Proceedings of 21st International Conference on Machine Learning (ICML-2004), pp. 81-88, Banff, Canada, July 2004.
Learnable Similarity Functions and Their Applications to Clustering and Record Linkage 2004
Mikhail Bilenko, In Proceedings of the Ninth AAAI/SIGART Doctoral Consortium, pp. 981--982, San Jose, CA, July 2004.
Semisupervised Clustering for Intelligent User Management 2004
Sugato Basu, Mikhail Bilenko, and Raymond J. Mooney, In Proceedings of the IBM Austin Center for Advanced Studies 5th Annual Austin CAS Conference, Austin, TX, February 2004.
Adaptive Duplicate Detection Using Learnable String Similarity Measures 2003
Mikhail Bilenko and Raymond J. Mooney, In Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2003), pp. 39-48, Washington, DC, August 2003.
Adaptive Name-Matching in Information Integration 2003
Mikhail Bilenko, William W. Cohen, Stephen Fienberg, Raymond J. Mooney, and Pradeep Ravikumar, IEEE Intelligent Systems, Vol. 18, 5 (2003), pp. 16-23.
Comparing and Unifying Search-Based and Similarity-Based Approaches to Semi-Supervised Clustering 2003
Sugato Basu, Mikhail Bilenko, and Raymond J. Mooney, In Proceedings of the ICML-2003 Workshop on the Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining, pp. 42-49, Washington, DC 2003.
Employing Trainable String Similarity Metrics for Information Integration 2003
Mikhail Bilenko and Raymond J. Mooney, In Proceedings of the IJCAI-03 Workshop on Information Integration on the Web, pp. 67-72, Acapulco, Mexico, August 2003.
Learnable Similarity Functions and Their Applications to Record Linkage and Clustering 2003
Mikhail Bilenko, unpublished. Doctoral Dissertation Proposal, University of Texas at Austin.
On Evaluation and Training-Set Construction for Duplicate Detection 2003
Mikhail Bilenko and Raymond J. Mooney, In Proceedings of the KDD-03 Workshop on Data Cleaning, Record Linkage, and Object Consolidation, pp. 7-12, Washington, DC, August 2003.
Learning to Combine Trained Distance Metrics for Duplicate Detection in Databases 2002
Mikhail Bilenko and Raymond J. Mooney, Technical Report AI 02-296, Artificial Intelligence Laboratory, University of Texas at Austin.
Two Approaches to Handling Noisy Variation in Text Mining 2002
Un Yong Nahm, Mikhail Bilenko, and Raymond J. Mooney, In Papers from the Nineteenth International Conference on Machine Learning (ICML-2002) Workshop on Text Learning, pp. 18-27, Sydney, Australia, July 2002.
Formerly affiliated with Machine Learning