| 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 | 3044 | 2008 |
| Handling missing values when applying classification models M Saar-Tsechansky, F Provost Journal of Machine Learning Research, 2007 | 528 | 2007 |
| Active sampling for class probability estimation and ranking M Saar-Tsechansky, F Provost Machine learning 54, 153-178, 2004 | 270 | 2004 |
| Active feature-value acquisition M Saar-Tsechansky, P Melville, F Provost Management Science 55 (4), 664-684, 2009 | 166 | 2009 |
| Dj-mc: A reinforcement-learning agent for music playlist recommendation E Liebman, M Saar-Tsechansky, P Stone arXiv preprint arXiv:1401.1880, 2014 | 144 | 2014 |
| A reinforcement learning approach to autonomous decision-making in smart electricity markets M Peters, W Ketter, M Saar-Tsechansky, J Collins Machine learning 92, 5-39, 2013 | 137 | 2013 |
| 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 | 123 | 2004 |
| Active learning for probability estimation using Jensen-Shannon divergence P Melville, SM Yang, M Saar-Tsechansky, R Mooney Machine Learning: ECML 2005: 16th European Conference on Machine Learning …, 2005 | 97 | 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 | 83 | 2005 |
| 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 | 80 | 2018 |
| 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 | 79 | 2019 |
| 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 | 74 | 2019 |
| Decision-centric active learning of binary-outcome models M Saar-Tsechansky, F Provost Information systems research 18 (1), 4-22, 2007 | 71 | 2007 |
| Algorithmic fairness in business analytics: Directions for research and practice M De‐Arteaga, S Feuerriegel, M Saar‐Tsechansky Production and Operations Management 31 (10), 3749-3770, 2022 | 70 | 2022 |
| Human-AI collaboration with bandit feedback R Gao, M Saar-Tsechansky, M De-Arteaga, L Han, MK Lee, M Lease arXiv preprint arXiv:2105.10614, 2021 | 58 | 2021 |
| Megastudy identifying effective interventions to strengthen Americans’ democratic attitudes JG Voelkel, M Stagnaro, J Chu, SL Pink, JS Mernyk, C Redekopp, ... OSF Preprints. March 20, 2023 | 55 | 2023 |
| 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 | 49 | 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 | 38 | 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 | 37 | 2006 |
| Editor’s comments: the business of business data science in IS journals M Saar-Tsechansky | 30 | 2015 |
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