Maytal Saar-Tsechansky
Cited by
Cited by
More than words: Quantifying language to measure firms' fundamentals
PC Tetlock, M Saar‐Tsechansky, S Macskassy
The journal of finance 63 (3), 1437-1467, 2008
Handling missing values when applying classification models
M Saar-Tsechansky, F Provost
Journal of Machine Learning Research, 2007
Active sampling for class probability estimation and ranking
M Saar-Tsechansky, F Provost
Machine learning 54 (2), 153-178, 2004
Active feature-value acquisition
M Saar-Tsechansky, P Melville, F Provost
Management Science 55 (4), 664-684, 2009
Active feature-value acquisition for classifier induction
P Melville, M Saar-Tsechansky, F Provost, R Mooney
Fourth IEEE International Conference on Data Mining (ICDM'04), 483-486, 2004
A reinforcement learning approach to autonomous decision-making in smart electricity markets
M Peters, W Ketter, M Saar-Tsechansky, J Collins
Machine learning 92 (1), 5-39, 2013
Active learning for probability estimation using Jensen-Shannon divergence
P Melville, SM Yang, M Saar-Tsechansky, R Mooney
European conference on machine learning, 268-279, 2005
An expected utility approach to active feature-value acquisition
P Melville, M Saar-Tsechansky, F Provost, R Mooney
Fifth IEEE International Conference on Data Mining (ICDM'05), 4 pp., 2005
Dj-mc: A reinforcement-learning agent for music playlist recommendation
E Liebman, M Saar-Tsechansky, P Stone
arXiv preprint arXiv:1401.1880, 2014
Decision-centric active learning of binary-outcome models
M Saar-Tsechansky, F Provost
Information systems research 18 (1), 4-22, 2007
Economical active feature-value acquisition through expected utility estimation
P Melville, F Provost, M Saar-Tsechansky, R Mooney
Proceedings of the 1st international workshop on Utility-based data mining …, 2005
Data acquisition and cost-effective predictive modeling: targeting offers for electronic commerce
F Provost, P Melville, M Saar-Tsechansky
Proceedings of the ninth international conference on Electronic commerce …, 2007
Adaptive mechanism design: a metalearning approach
D Pardoe, P Stone, M Saar-Tsechansky, K Tomak
Proceedings of the 8th international conference on Electronic commerce: The …, 2006
Guest editorial: special issue on utility-based data mining
GM Weiss, B Zadrozny, M Saar-Tsechansky
Data Mining and Knowledge Discovery 17 (2), 129, 2008
Information systems for a smart electricity grid: Emerging challenges and opportunities
W Ketter, J Collins, M Saar-Tsechansky, O Marom
ACM Transactions on Management Information Systems (TMIS) 9 (3), 1-22, 2018
The Right Music at the Right Time: Adaptive Personalized Playlists Based on Sequence Modeling.
E Liebman, M Saar-Tsechansky, P Stone
MIS Quarterly 43 (3), 2019
Using retweets when shaping our online persona: Topic modeling approach
H Geva, G Oestreicher-Singer, M Saar-Tsechansky
MIS Quarterly 43 (2), 501-524, 2019
Adaptive auction mechanism design and the incorporation of prior knowledge
D Pardoe, P Stone, M Saar-Tsechansky, T Keskin, K Tomak
INFORMS journal on Computing 22 (3), 353-370, 2010
Editor’s comments: The business of business data science in IS journals
M Saar-Tsechansky
Collaborative information acquisition for data-driven decisions
D Kong, M Saar-Tsechansky
Machine learning 95 (1), 71-86, 2014
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