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Dachao Lin
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2020 – today
- 2024
- [i11]Jing Li, Zhijie Sun, Dachao Lin, Xuan He, Yi Lin, Binfan Zheng, Li Zeng, Rongqian Zhao, Xin Chen:
LocMoE+: Enhanced Router with Token Feature Awareness for Efficient LLM Pre-Training. CoRR abs/2406.00023 (2024) - 2023
- [j3]Haishan Ye, Dachao Lin, Xiangyu Chang
, Zhihua Zhang:
Towards explicit superlinear convergence rate for SR1. Math. Program. 199(1): 1273-1303 (2023) - [c6]Dachao Lin, Yuze Han, Haishan Ye, Zhihua Zhang:
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis. NeurIPS 2023 - [i10]Dachao Lin, Yuze Han, Haishan Ye, Zhihua Zhang:
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis. CoRR abs/2304.07504 (2023) - 2022
- [j2]Dachao Lin
, Ruoyu Sun, Zhihua Zhang:
On the landscape of one-hidden-layer sparse networks and beyond. Artif. Intell. 309: 103739 (2022) - [j1]Dachao Lin, Haishan Ye, Zhihua Zhang:
Explicit Convergence Rates of Greedy and Random Quasi-Newton Methods. J. Mach. Learn. Res. 23: 162:1-162:40 (2022) - [c5]Kun Chen, Dachao Lin, Zhihua Zhang:
On Non-local Convergence Analysis of Deep Linear Networks. ICML 2022: 3417-3443 - [i9]Kun Chen, Dachao Lin, Zhihua Zhang:
Global Convergence Analysis of Deep Linear Networks with A One-neuron Layer. CoRR abs/2201.02761 (2022) - [i8]Dachao Lin, Zhihua Zhang:
On the Convergence of Policy in Unregularized Policy Mirror Descent. CoRR abs/2205.08176 (2022) - 2021
- [c4]Dachao Lin, Ruoyu Sun, Zhihua Zhang:
Faster Directional Convergence of Linear Neural Networks under Spherically Symmetric Data. NeurIPS 2021: 4647-4660 - [c3]Dachao Lin, Haishan Ye, Zhihua Zhang:
Greedy and Random Quasi-Newton Methods with Faster Explicit Superlinear Convergence. NeurIPS 2021: 6646-6657 - [i7]Guangzeng Xie, Hao Jin, Dachao Lin, Zhihua Zhang:
Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent. CoRR abs/2104.05447 (2021) - [i6]Dachao Lin, Zhihua Zhang:
Directional Convergence Analysis under Spherically Symmetric Distribution. CoRR abs/2105.03879 (2021) - [i5]Haishan Ye, Dachao Lin, Zhihua Zhang:
Greedy and Random Broyden's Methods with Explicit Superlinear Convergence Rates in Nonlinear Equations. CoRR abs/2110.08572 (2021) - 2020
- [i4]Dachao Lin, Peiqin Sun, Guangzeng Xie, Shuchang Zhou, Zhihua Zhang:
Optimal Quantization for Batch Normalization in Neural Network Deployments and Beyond. CoRR abs/2008.13128 (2020) - [i3]Dachao Lin, Ruoyu Sun, Zhihua Zhang:
Landscape of Sparse Linear Network: A Brief Investigation. CoRR abs/2009.07439 (2020)
2010 – 2019
- 2019
- [c2]Mo Zhou, Tianyi Liu, Yan Li, Dachao Lin, Enlu Zhou, Tuo Zhao:
Toward Understanding the Importance of Noise in Training Neural Networks. ICML 2019: 7594-7602 - [i2]Hao Jin, Dachao Lin, Zhihua Zhang:
Towards Better Generalization: BP-SVRG in Training Deep Neural Networks. CoRR abs/1908.06395 (2019) - [i1]Mo Zhou, Tianyi Liu, Yan Li, Dachao Lin, Enlu Zhou, Tuo Zhao:
Towards Understanding the Importance of Noise in Training Neural Networks. CoRR abs/1909.03172 (2019) - 2010
- [c1]Jinshun Wu, Dachao Lin, Genyin Cheng, Weijie Zhang:
Application research of comprehensive evaluation based on the theory of unascertainty measure. FSKD 2010: 1101-1104
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