66 citations · 74 across the 5 of their papers we have counts for
5 papers
ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency
Chuming Li, Jie Liu, Yinmin Zhang +5
Multi-agent reinforcement learning (MARL) suffers from the non-stationarity problem, which is the ever-changing targets at every iteration when multiple agents update their policie…
Adaptive Gradient Method with Resilience and Momentum
Jie Liu, Chen Lin, Chuming Li +4
Several variants of stochastic gradient descent (SGD) have been proposed to improve the learning effectiveness and efficiency when training deep neural networks, among which some r…
On the Acceleration of L-BFGS with Second-Order Information and Stochastic Batches
Jie Liu, Yu Rong, Martin Takac +1
This paper proposes a framework of L-BFGS based on the (approximate) second-order information with stochastic batches, as a novel approach to the finite-sum minimization problems.…
MLE-induced Likelihood for Markov Random Fields
Jie Liu, Hao Zheng
Due to the intractable partition function, the exact likelihood function for a Markov random field (MRF), in many situations, can only be approximated. Major approximation approach…
Stochastic Recursive Gradient Algorithm for Nonconvex Optimization
Lam M. Nguyen, Jie Liu, Katya Scheinberg +1
In this paper, we study and analyze the mini-batch version of StochAstic Recursive grAdient algoritHm (SARAH), a method employing the stochastic recursive gradient, for solving emp…