1 citations · 2 across the 11 of their papers we have counts for
6 papers · 1 filter
Spectral Collapse Drives Loss of Plasticity in Deep Continual Learning
Arjun Prakash, Naicheng He, Kaicheng Guo +5
We investigate why deep neural networks suffer from loss of plasticity in continual learning, and thus fail to learn new tasks without reinitializing parameters. We show that this…
Bi-Level Policy Optimization with Nyström Hypergradients
Arjun Prakash, Naicheng He, Denizalp Goktas +2
The dependency of the actor on the critic in actor-critic (AC) reinforcement learning means that AC can be characterized as a bilevel optimization (BLO) problem, also called a Stac…
Efficient Inverse Multiagent Learning
Denizalp Goktas, Amy Greenwald, Sadie Zhao +2
In this paper, we study inverse game theory (resp. inverse multiagent learning) in which the goal is to find parameters of a game's payoff functions for which the expected (resp. s…
Infinite Horizon Markov Economies
Denizalp Goktas, Sadie Zhao, Yiling Chen +1
In this paper, we study a generalization of Markov games and pseudo-games that we call Markov pseudo-games, which, like the former, captures time and uncertainty, and like the latt…
Tractable General Equilibrium
Denizalp Goktas, Klára Chura, Alp Emin Guneri +1
We study Walrasian economies (or general equilibrium models) and their solution concept, the Walrasian equilibrium. A key challenge in this domain is identifying price-adjustment p…
Banzhaf Power in Hierarchical Voting Games
John Randolph, Denizalp Goktas, Amy Greenwald
The Banzhaf Power Index (BPI) is a method of measuring the power of voters in determining the outcome of a voting game. Some voting games exhibit a hierarchical structure, includin…