101 citations · 192 across the 6 of their papers we have counts for
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cs.LG2020★ 101 cited
Finite-Sample Analysis of Proximal Gradient TD Algorithms
Bo Liu, Ji Liu, Mohammad Ghavamzadeh +2
In this paper, we analyze the convergence rate of the gradient temporal difference learning (GTD) family of algorithms. Previous analyses of this class of algorithms use ODE techni…
cs.LG2020★ 19 cited
Regularized Off-Policy TD-Learning
Bo Liu, Sridhar Mahadevan, Ji Liu
We present a novel regularized off-policy convergent TD-learning method (termed RO-TD), which is able to learn sparse representations of value functions with low computationa…
cs.LG2020★ 5 cited
Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity
Bo Liu, Ian Gemp, Mohammad Ghavamzadeh +3
In this paper, we introduce proximal gradient temporal difference learning, which provides a principled way of designing and analyzing true stochastic gradient temporal difference…