219 citations · 1.6k across the 95 of their papers we have counts for
10 papers · 1 filter
Provably Efficient Cooperative Multi-Agent Reinforcement Learning with Function Approximation
Abhimanyu Dubey, Alex Pentland
Reinforcement learning in cooperative multi-agent settings has recently advanced significantly in its scope, with applications in cooperative estimation for advertising, dynamic tr…
Differentially-Private Federated Linear Bandits
Abhimanyu Dubey, Alex Pentland
The rapid proliferation of decentralized learning systems mandates the need for differentially-private cooperative learning. In this paper, we study this in context of the contextu…
Cooperative Multi-Agent Bandits with Heavy Tails
Abhimanyu Dubey, Alex Pentland
We study the heavy-tailed stochastic bandit problem in the cooperative multi-agent setting, where a group of agents interact with a common bandit problem, while communicating on a…
Kernel Methods for Cooperative Multi-Agent Contextual Bandits
Abhimanyu Dubey, Alex Pentland
Cooperative multi-agent decision making involves a group of agents cooperatively solving learning problems while communicating over a network with delays. In this paper, we conside…
A Study of Compositional Generalization in Neural Models
Tim Klinger, Dhaval Adjodah, Vincent Marois +4
Compositional and relational learning is a hallmark of human intelligence, but one which presents challenges for neural models. One difficulty in the development of such models is…
DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning
Michiel A. Bakker, Duy Patrick Tu, Humberto Riverón Valdés +4
We introduce a framework for dynamic adversarial discovery of information (DADI), motivated by a scenario where information (a feature set) is used by third parties with unknown ob…