306 citations · 817 across the 31 of their papers we have counts for
4 papers · 1 filter
Target Transfer Q-Learning and Its Convergence Analysis
Yue Wang, Qi Meng, Wei Cheng +3
Q-learning is one of the most popular methods in Reinforcement Learning (RL). Transfer Learning aims to utilize the learned knowledge from source tasks to help new tasks to improve…
Capacity Control of ReLU Neural Networks by Basis-path Norm
Shuxin Zheng, Qi Meng, Huishuai Zhang +3
Recently, path norm was proposed as a new capacity measure for neural networks with Rectified Linear Unit (ReLU) activation function, which takes the rescaling-invariant property o…
Differential Equations for Modeling Asynchronous Algorithms
Li He, Qi Meng, Wei Chen +2
Asynchronous stochastic gradient descent (ASGD) is a popular parallel optimization algorithm in machine learning. Most theoretical analysis on ASGD take a discrete view and prove u…
-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
Qi Meng, Shuxin Zheng, Huishuai Zhang +3
It is well known that neural networks with rectified linear units (ReLU) activation functions are positively scale-invariant. Conventional algorithms like stochastic gradient desce…