101 citations · 169 across the 6 of their papers we have counts for
6 papers
Convergent Actor-Critic Algorithms Under Off-Policy Training and Function Approximation
Hamid Reza Maei
We present the first class of policy-gradient algorithms that work with both state-value and policy function-approximation, and are guaranteed to converge under off-policy training…
Deep Reinforcement Learning for Visual Object Tracking in Videos
Da Zhang, Hamid Maei, Xin Wang +1
In this paper we introduce a fully end-to-end approach for visual tracking in videos that learns to predict the bounding box locations of a target object at every frame. An importa…
A Batch, Off-Policy, Actor-Critic Algorithm for Optimizing the Average Reward
S. A. Murphy, Y. Deng, E. B. Laber +3
We develop an off-policy actor-critic algorithm for learning an optimal policy from a training set composed of data from multiple individuals. This algorithm is developed with a vi…
Optimal Demand Response Using Device Based Reinforcement Learning
Zheng Wen, Daniel O'Neill, Hamid Reza Maei
Demand response (DR) for residential and small commercial buildings is estimated to account for as much as 65% of the total energy savings potential of DR, and previous work shows…
Correlated quantum percolation in the lowest Landau level
Nancy Sandler, Hamid Maei, Jane' Kondev
Our understanding of localization in the integer quantum Hall effect is informed by a combination of semi-classical models and percolation theory. Motivated by the effect of correl…
Quantum and classical localization in the lowest Landau level
N. Sandler, H. Maei, J. Kondev
Spatial correlations of occupation probabilities, if their decay is not too fast, can change the critical exponents for classical percolation. From numerical studies of electron dy…