13 citations · 43 across the 11 of their papers we have counts for
6 papers · 1 filter
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…
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…