Search Results for author: Zaiyi Chen

Found 9 papers, 1 papers with code

Stochastic Continuous Submodular Maximization: Boosting via Non-oblivious Function

no code implementations3 Jan 2022 Qixin Zhang, Zengde Deng, Zaiyi Chen, Haoyuan Hu, Yu Yang

In the online setting, for the first time we consider the adversarial delays for stochastic gradient feedback, under which we propose a boosting online gradient algorithm with the same non-oblivious function $F$.

Online Allocation with Two-sided Resource Constraints

no code implementations28 Dec 2021 Qixin Zhang, Wenbing Ye, Zaiyi Chen, Haoyuan Hu, Enhong Chen, Yang Yu

Moreover, an optimization method to estimate the optimal measure of feasibility is proposed with theoretical guarantee at the end of this paper.

Adam revisited: a weighted past gradients perspective

no code implementations1 Jan 2021 Hui Zhong, Zaiyi Chen, Chuan Qin, Zai Huang, Vincent W. Zheng, Tong Xu, Enhong Chen

Though many algorithms, such as AMSGRAD and ADAMNC, have been proposed to fix the non-convergence issues, achieving a data-dependent regret bound similar to or better than ADAGRAD is still a challenge to these methods.

Symmetric Cross Entropy for Robust Learning with Noisy Labels

3 code implementations ICCV 2019 Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jin-Feng Yi, James Bailey

In this paper, we show that DNN learning with Cross Entropy (CE) exhibits overfitting to noisy labels on some classes ("easy" classes), but more surprisingly, it also suffers from significant under learning on some other classes ("hard" classes).

Learning with noisy labels

Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation

no code implementations10 Jun 2019 Dong-Dong Chen, Yisen Wang, Jin-Feng Yi, Zaiyi Chen, Zhi-Hua Zhou

Unsupervised domain adaptation aims to transfer the classifier learned from the source domain to the target domain in an unsupervised manner.

Unsupervised Domain Adaptation

Efficient Rank Minimization via Solving Non-convexPenalties by Iterative Shrinkage-Thresholding Algorithm

no code implementations14 Sep 2018 Zaiyi Chen

Rank minimization (RM) is a wildly investigated task of finding solutions by exploiting low-rank structure of parameter matrices.

Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions

no code implementations ICLR 2019 Zaiyi Chen, Zhuoning Yuan, Jin-Feng Yi, Bo-Wen Zhou, Enhong Chen, Tianbao Yang

For example, there is still a lack of theories of convergence for SGD and its variants that use stagewise step size and return an averaged solution in practice.

SADAGRAD: Strongly Adaptive Stochastic Gradient Methods

no code implementations ICML 2018 Zaiyi Chen, Yi Xu, Enhong Chen, Tianbao Yang

Although the convergence rates of existing variants of ADAGRAD have a better dependence on the number of iterations under the strong convexity condition, their iteration complexities have a explicitly linear dependence on the dimensionality of the problem.

Fast Stochastic AUC Maximization with $O(1/n)$-Convergence Rate

no code implementations ICML 2018 Mingrui Liu, Xiaoxuan Zhang, Zaiyi Chen, Xiaoyu Wang, Tianbao Yang

In this paper, we consider statistical learning with AUC (area under ROC curve) maximization in the classical stochastic setting where one random data drawn from an unknown distribution is revealed at each iteration for updating the model.

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