51 citations · 55 across the 2 of their papers we have counts for
6 papers
Adam revisited: a weighted past gradients perspective
Hui Zhong, Zaiyi Chen, Chuan Qin +4
Adaptive learning rate methods have been successfully applied in many fields, especially in training deep neural networks. Recent results have shown that adaptive methods with expo…
Symmetric Cross Entropy for Robust Learning with Noisy Labels
Yisen Wang, Xingjun Ma, Zaiyi Chen +3
Training accurate deep neural networks (DNNs) in the presence of noisy labels is an important and challenging task. Though a number of approaches have been proposed for learning wi…
Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation
Dong-Dong Chen, Yisen Wang, Jinfeng Yi +2
Unsupervised domain adaptation aims to transfer the classifier learned from the source domain to the target domain in an unsupervised manner. With the help of target pseudo-labels,…
Efficient Rank Minimization via Solving Non-convexPenalties by Iterative Shrinkage-Thresholding Algorithm
Zaiyi Chen
Rank minimization (RM) is a wildly investigated task of finding solutions by exploiting low-rank structure of parameter matrices. Recently, solving RM problem by leveraging non-con…
Katalyst: Boosting Convex Katayusha for Non-Convex Problems with a Large Condition Number
Zaiyi Chen, Yi Xu, Haoyuan Hu +1
In this paper, we propose a new SVRG-style acceleated stochastic algorithm for solving a family of non-convex optimization problems whose objective consists of a sum of smooth…
Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions
Zaiyi Chen, Zhuoning Yuan, Jinfeng Yi +3
Although stochastic gradient descent (SGD) method and its variants (e.g., stochastic momentum methods, AdaGrad) are the choice of algorithms for solving non-convex problems (especi…