36 citations · 165 across the 31 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.LG2023
TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models
Zuxin Liu, Jesse Zhang, Kavosh Asadi +4
The full potential of large pretrained models remains largely untapped in control domains like robotics. This is mainly because of the scarcity of data and the computational challe…
cs.LG2023★ 3 cited
Resetting the Optimizer in Deep RL: An Empirical Study
Kavosh Asadi, Rasool Fakoor, Shoham Sabach
We focus on the task of approximating the optimal value function in deep reinforcement learning. This iterative process is comprised of solving a sequence of optimization problems…
cs.LG2023
TD Convergence: An Optimization Perspective
Kavosh Asadi, Shoham Sabach, Yao Liu +2
We study the convergence behavior of the celebrated temporal-difference (TD) learning algorithm. By looking at the algorithm through the lens of optimization, we first argue that T…