Maytal Saar-Tsechansky
Affiliated Faculty
I am interested in various aspects of automatic learning of patterns from data to support decision making in organizations. Recently I have been focusing primarily on learning from customer/user behavior. Advances in information and computer technology and the growing availability of data underlie the explosion of methods in machine learning, data mining and applied statistics for automatic discovery of patterns in data. The prospects of utilizing these methods to advance businesses and organizations have driven much of their widespread employment in business. In light of the growing importance of such practices I am particularly interested in studying the technological challenges facing data mining and machine learning approaches to couple tightly with business and organizational objectives.
Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge 2010
David Pardoe, Peter Stone, Maytal Saar-Tsechansky, Tayfun Keskin, and Kerem Tomak, Informs Journal on Computing, Vol. 22, 3 (2010), pp. 353-370.
Adaptive Mechanism Design: A Metalearning Approach 2006
David Pardoe, Peter Stone, Maytal Saar-Tsechansky, and Kerem Tomak, In The Eighth International Conference on Electronic Commerce, pp. 92-102, August 2006.
Active Learning for Probability Estimation using Jensen-Shannon Divergence 2005
P. Melville, S. M. Yang, M. Saar-Tsechansky and Raymond J. Mooney, In Proceedings of the 16th European Conference on Machine Learning, pp. 268--279, Porto, Portugal, October 2005.
An Expected Utility Approach to Active Feature-value Acquisition 2005
P. Melville, M. Saar-Tsechansky, F. Provost and Raymond J. Mooney, In Proceedings of the International Conference on Data Mining, pp. 745-748, Houston, TX, November 2005.
Economical Active Feature-value Acquisition through Expected Utility Estimation 2005
P. Melville, M. Saar-Tsechansky, F. Provost and Raymond J. Mooney, In Proceedings of the KDD-05 Workshop on Utility-Based Data Mining, pp. 10-16, Chicago, IL, August 2005.
Active Feature-Value Acquisition for Classifier Induction 2004
Prem Melville, Maytal Saar-Tsechansky, Foster Provost, and Raymond J. Mooney, Technical Report UT-AI-TR-04-311, Artificial Intelligence Lab, University of Texas at Austin.
Active Feature-Value Acquisition for Classifier Induction 2004
Prem Melville, Maytal Saar-Tsechansky, Foster Provost, and Raymond J. Mooney, In Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM-2004), pp. 483-486, Brighton, UK, November 2004.
Currently affiliated with