Saar-Tsechansky, Maytal

12 publications

NeurIPS 2024 SEL-BALD: Deep Bayesian Active Learning with Selective Labels Ruijiang Gao, Mingzhang Yin, Maytal Saar-Tsechansky

IJCAI 2021 Human-AI Collaboration with Bandit Feedback Ruijiang Gao, Maytal Saar-Tsechansky, Maria De-Arteaga, Ligong Han, Min Kyung Lee, Matthew Lease

AAAI 2020 Cost-Accuracy Aware Adaptive Labeling for Active Learning Ruijiang Gao, Maytal Saar-Tsechansky

MLJ 2018 A Scalable Preference Model for Autonomous Decision-Making Markus Peters, Maytal Saar-Tsechansky, Wolfgang Ketter, Sinead A. Williamson, Perry Groot, Tom Heskes

AAAI 2017 Designing Better Playlists with Monte Carlo Tree Search Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, Peter Stone

MLJ 2014 Collaborative Information Acquisition for Data-Driven Decisions Danxia Kong, Maytal Saar-Tsechansky

MLJ 2013 A Reinforcement Learning Approach to Autonomous Decision-Making in Smart Electricity Markets Markus Peters, Wolfgang Ketter, Maytal Saar-Tsechansky, John Collins

ECML-PKDD 2012 Autonomous Data-Driven Decision-Making in Smart Electricity Markets Markus Peters, Wolfgang Ketter, Maytal Saar-Tsechansky, John Collins

JMLR 2007 Handling Missing Values When Applying Classification Models Maytal Saar-Tsechansky, Foster Provost

ECML-PKDD 2005 Active Learning for Probability Estimation Using Jensen-Shannon Divergence Prem Melville, Stewart M. Yang, Maytal Saar-Tsechansky, Raymond J. Mooney

MLJ 2004 Active Sampling for Class Probability Estimation and Ranking Maytal Saar-Tsechansky, Foster J. Provost

IJCAI 2001 Active Learning for Class Probability Estimation and Ranking Maytal Saar-Tsechansky, Foster J. Provost