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Haishan Ye
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Publications
- 2024
- [c14]Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor W. Tsang, Yong Liu:
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold. ICLR 2024 - [c13]Hao Di, Haishan Ye, Xiangyu Chang, Guang Dai, Ivor W. Tsang:
Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods. ICML 2024 - [c12]Hao Di, Haishan Ye, Yueling Zhang, Xiangyu Chang, Guang Dai, Ivor W. Tsang:
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient. ICML 2024 - [c11]Yilong Wang, Haishan Ye, Guang Dai, Ivor W. Tsang:
Can Gaussian Sketching Converge Faster on a Preconditioned Landscape? ICML 2024 - [i26]Yanjun Zhao, Sizhe Dang, Haishan Ye, Guang Dai, Yi Qian, Ivor W. Tsang:
Second-Order Fine-Tuning without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer. CoRR abs/2402.15173 (2024) - [i24]Hao Di, Haishan Ye, Yueling Zhang, Xiangyu Chang, Guang Dai, Ivor W. Tsang:
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient. CoRR abs/2405.17761 (2024) - 2023
- [i21]Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor W. Tsang
, Yong Liu:
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold. CoRR abs/2308.10547 (2023)

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