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Kaiwen Zhou
Kaiwen Zhou
Verified email at cse.cuhk.edu.hk - Homepage
Title
Cited by
Cited by
Year
A simple stochastic variance reduced algorithm with fast convergence rates
K Zhou, F Shang, J Cheng
International Conference on Machine Learning (ICML) 80, 5980-5989, 2018
912018
VR-SGD: A simple stochastic variance reduction method for machine learning
F Shang, K Zhou, H Liu, J Cheng, IW Tsang, L Zhang, D Tao, L Jiao
IEEE Transactions on Knowledge and Data Engineering 32 (1), 188-202, 2018
672018
Direct acceleration of SAGA using sampled negative momentum
K Zhou, Q Ding, F Shang, J Cheng, D Li, ZQ Luo
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2019
612019
Hyper-sphere quantization: Communication-efficient SGD for federated learning
X Dai, X Yan, K Zhou, H Yang, KKW Ng, J Cheng, Y Fan
arXiv preprint arXiv:1911.04655, 2019
462019
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization
Y Chen, K Zhou, Y Bian, B Xie, B Wu, Y Zhang, MA KAILI, H Yang, P Zhao, ...
International Conference on Learning Representations (ICLR), 2023
332023
ASVRG: accelerated proximal SVRG
F Shang, L Jiao, K Zhou, J Cheng, Y Ren, Y Jin
Asian Conference on Machine Learning, 815-830, 2018
302018
Convolutional embedding for edit distance
X Dai, X Yan, K Zhou, Y Wang, H Yang, J Cheng
International ACM SIGIR Conference on Research and Development in …, 2020
24*2020
On the Finite-Time Complexity and Practical Computation of Approximate Stationarity Concepts of Lipschitz Functions
L Tian, K Zhou, AMC So
International Conference on Machine Learning (ICML), 21360-21379, 2022
23*2022
Guaranteed sufficient decrease for stochastic variance reduced gradient optimization
F Shang, Y Liu, K Zhou, J Cheng, KKW Ng, Y Yoshida
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2018
122018
Understanding and Improving Feature Learning for Out-of-Distribution Generalization
Y Chen, W Huang, K Zhou, Y Bian, B Han, J Cheng
Advances in Neural Information Processing Systems (NeurIPS), 2023
11*2023
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums
K Zhou, L Tian, AMC So, J Cheng
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021
112021
Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
Y Chen, Y Bian, K Zhou, B Xie, B Han, J Cheng
Advances in Neural Information Processing Systems (NeurIPS), 2023
8*2023
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack
R Gao, J Wang, K Zhou, F Liu, B Xie, G Niu, B Han, J Cheng
International Conference on Machine Learning (ICML), 7144-7163, 2022
82022
Amortized Nesterov’s Momentum: A Robust Momentum and Its Application to Deep Learning
K Zhou, Y Jin, Q Ding, J Cheng
Conference on Uncertainty in Artificial Intelligence (UAI) 124, 211-220, 2020
82020
Boosting First-order Methods by Shifting Objective: New Schemes with Faster Worst Case Rates
K Zhou, AMC So, J Cheng
Advances in Neural Information Processing Systems (NeurIPS), 15405–15416, 2020
62020
Tight Convergence Rate of Gradient Descent for Eigenvalue Computation
Q Ding, K Zhou, J Cheng
International Joint Conference on Artificial Intelligence (IJCAI), 2020
52020
Efficient private sco for heavy-tailed data via clipping
C Jin, K Zhou, B Han, MC Yang, J Cheng
arXiv preprint arXiv:2206.13011, 2022
32022
Local reweighting for adversarial training
R Gao, F Liu, K Zhou, G Niu, B Han, J Cheng
arXiv preprint arXiv:2106.15776, 2021
32021
A novel extrapolation technique to accelerate WMMSE
K Zhou, Z Chen, G Liu, Z Chen
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023
22023
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization
K Zhou, AMC So, J Cheng
NeurIPS 2022 Workshop on Optimization for Machine Learning (NeurIPS OPT), 2022
12022
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