Elad Liebman
Ph.D. Student
Elad is interested in machine learning and its application in autonomous multiagent settings, as well as the emergent field of computational musicology. Before coming to UT he did his undergrad in CS and music composition (double-major program) and a MSc in CS, both at Tel Aviv University (his Masters thesis subject: A Phylogenetic Approach to Music Performance Analysis). Elad's current work focuses on learning musical preferences and modeling the effect of musical stimuli on human decision making. In his free time, Elad enjoys music in every way and form (listening to it, playing the piano and the guitar, and writing his own), reading (anything from classic literature and philosophy to the sports section), cooking, and playing racquetball.
     [Expand to show all 11][Minimize]
Decision mechanisms underlying mood-congruent emotional classification 2017
Corey White, Elad Liebman, and Peter Stone, Cognition and Emotion (2017), pp. 1--10. Taylor and Francis.
Designing Better Playlists with Monte Carlo Tree Search 2017
Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, and Peter Stone, In PROCEEDINGS OF THE TWENTY-NINTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE (IAAI-17), San Francisco, USA, February 2017.
Fast and Precise Black and White Ball Detection for RoboCup Soccer 2017
Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, and Peter Stone, In {R}obo{C}up-2017: Robot Soccer World Cup {XXI}, 2017 (Eds.), Nagoya, Japan, July 2017.
Adaptation of Surrogate Tasks for Bipedal Walk Optimization 2016
Patrick MacAlpine, Elad Liebman, and Peter Stone, In GECCO Surrogate-Assisted Evolutionary Optimisation (SAEOpt) Workshop, Denver, Colorado, USA, July 2016.
On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search 2016
Khandelwal, Piyush, Liebman, Elad, Niekum, Scott, Stone, and Peter, In Proceedings of The 33rd International Conference on Machine Learning, pp. 1319--1328, New York City, NY, USA, June 2016.
Bin-Based Estimation of the Amount of Effort for Embedded Software Development Projects with Support Vector Machines 2016
Kazunori Iwata, Elad Liebman, Peter Stone, Toyoshiro Nakashima, Yoshiyuki Anan, and Naohiro Ishii, In {C}omputer and {I}nformation {S}cience , Roger Lee (Eds.), Berlin 2016. Springer Verlag.
Impact of Music on Decision Making in Quantitative Tasks 2016
Elad Liebman, Peter Stone, and Corey N. White, In 17th International Society for Music Information retrieval Conference (ISMIR), NYC, USA, August 2016.
DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation 2015
Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone, In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Istanbul, Turkey, May 2015.
How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification 2015
Elad Liebman, Peter Stone, and Corey N. White, In 16th International Society for Music Information Retrieval Conference (ISMIR), Malaga, Spain, October 2015.
Representative Selection in Nonmetric Datasets 2015
Elad Liebman, Benny Chor, and Peter Stone, Applied Artificial Intelligence, Vol. 29, 8 (2015), pp. 807--838.
Simultaneous Learning and Reshaping of an Approximated Optimization Task 2013
Patrick MacAlpine, Elad Liebman, and Peter Stone, In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2013.
Currently affiliated with Learning Agents