13 citations · 43 across the 11 of their papers we have counts for
11 papers
Complex contraction on trees without proof of correlation decay
Liang Li, Guangzeng Xie
We prove complex contraction for zero-free regions of counting weighted set cover problem in which an element can appear in an unbounded number of sets, thus obtaining fully polyno…
Near Optimal Stochastic Algorithms for Finite-Sum Unbalanced Convex-Concave Minimax Optimization
Luo Luo, Guangzeng Xie, Tong Zhang +1
This paper considers stochastic first-order algorithms for convex-concave minimax problems of the form , where can be presented by the…
Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent
Guangzeng Xie, Hao Jin, Dachao Lin +1
We propose \textit{Meta-Regularization}, a novel approach for the adaptive choice of the learning rate in first-order gradient descent methods. Our approach modifies the objective…
DIPPA: An improved Method for Bilinear Saddle Point Problems
Guangzeng Xie, Yuze Han, Zhihua Zhang
This paper studies bilinear saddle point problems , where the functions are smooth and stron…
Lower Complexity Bounds of Finite-Sum Optimization Problems: The Results and Construction
Yuze Han, Guangzeng Xie, Zhihua Zhang
In this paper, we study the lower complexity bounds for finite-sum optimization problems, where the objective is the average of individual component functions. We consider Prox…
Finding the Near Optimal Policy via Adaptive Reduced Regularization in MDPs
Wenhao Yang, Xiang Li, Guangzeng Xie +1
Regularized MDPs serve as a smooth version of original MDPs. However, biased optimal policy always exists for regularized MDPs. Instead of making the coefficientλof regularized ter…
Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices
Luo Luo, Cheng Chen, Guangzeng Xie +1
We study the streaming model for approximate matrix multiplication (AMM). We are interested in the scenario that the algorithm can only take one pass over the data with limited mem…
Optimal Quantization for Batch Normalization in Neural Network Deployments and Beyond
Dachao Lin, Peiqin Sun, Guangzeng Xie +2
Quantized Neural Networks (QNNs) use low bit-width fixed-point numbers for representing weight parameters and activations, and are often used in real-world applications due to thei…
A Stochastic Proximal Point Algorithm for Saddle-Point Problems
Luo Luo, Cheng Chen, Yujun Li +2
We consider saddle point problems which objective functions are the average of strongly convex-concave individual components. Recently, researchers exploit variance reduction m…
A General Analysis Framework of Lower Complexity Bounds for Finite-Sum Optimization
Guangzeng Xie, Luo Luo, Zhihua Zhang
This paper studies the lower bound complexity for the optimization problem whose objective function is the average of individual smooth convex functions. We consider the algori…
Interpolatron: Interpolation or Extrapolation Schemes to Accelerate Optimization for Deep Neural Networks
Guangzeng Xie, Yitan Wang, Shuchang Zhou +1
In this paper we explore acceleration techniques for large scale nonconvex optimization problems with special focuses on deep neural networks. The extrapolation scheme is a classic…