9 citations · 26 across the 8 of their papers we have counts for
9 papers
Sequence Modeling for N-Agent Ad Hoc Teamwork
Caroline Wang, Di Yang Shi, Elad Liebman +3
N-agent ad hoc teamwork (NAHT) is a newly introduced challenge in multi-agent reinforcement learning, where controlled subteams of varying sizes must dynamically collaborate with v…
Seismic Image Denoising With A Physics-Constrained Deep Image Prior
Dimitri P. Voytan, Sriram Ravula, Alexandru Ardel +4
Seismic images often contain both coherent and random artifacts which complicate their interpretation. To mitigate these artifacts, we introduce a novel unsupervised deep-learning…
Pattern-Based Time-Series Risk Scoring for Anomaly Detection and Alert Filtering -- A Predictive Maintenance Case Study
Elad Liebman
Fault detection is a key challenge in the management of complex systems. In the context of SparkCognition's efforts towards predictive maintenance in large scale industrial systems…
N-Agent Ad Hoc Teamwork
Caroline Wang, Arrasy Rahman, Ishan Durugkar +2
Current approaches to learning cooperative multi-agent behaviors assume relatively restrictive settings. In standard fully cooperative multi-agent reinforcement learning, the learn…
Utilizing Mood-Inducing Background Music in Human-Robot Interaction
Elad Liebman, Peter Stone
Past research has clearly established that music can affect mood and that mood affects emotional and cognitive processing, and thus decision-making. It follows that if a robot inte…
DM: Decentralized Multi-Agent Reinforcement Learning for Distribution Matching
Caroline Wang, Ishan Durugkar, Elad Liebman +1
Current approaches to multi-agent cooperation rely heavily on centralized mechanisms or explicit communication protocols to ensure convergence. This paper studies the problem of di…
Artificial Musical Intelligence: A Survey
Elad Liebman, Peter Stone
Computers have been used to analyze and create music since they were first introduced in the 1950s and 1960s. Beginning in the late 1990s, the rise of the Internet and large scale…
Representative Selection in Non Metric Datasets
Elad Liebman, Benny Chor, Peter Stone
This paper considers the problem of representative selection: choosing a subset of data points from a dataset that best represents its overall set of elements. This subset needs to…
DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation
Elad Liebman, Maytal Saar-Tsechansky, Peter Stone
In recent years, there has been growing focus on the study of automated recommender systems. Music recommendation systems serve as a prominent domain for such works, both from an a…