Application research of comprehensive evaluation based on the theory of unascertainty measure. - Jinshun Wu; Dachao Lin; Genyin Cheng; Weijie Zhang (FSKD, 2010)

Toward Understanding the Importance of Noise in Training Neural Networks. - Mo Zhou; Tianyi Liu; Yan Li 074; Dachao Lin; Enlu Zhou; Tuo Zhao (ICML, 2019)

Towards Better Generalization: BP-SVRG in Training Deep Neural Networks. - Hao Jin; Dachao Lin; Zhihua Zhang 004 (CoRR, 2019)

Towards Understanding the Importance of Noise in Training Neural Networks. - Mo Zhou; Tianyi Liu; Yan Li 074; Dachao Lin; Enlu Zhou; Tuo Zhao (CoRR, 2019)

Optimal Quantization for Batch Normalization in Neural Network Deployments and Beyond. - Dachao Lin; Peiqin Sun; Guangzeng Xie; Shuchang Zhou 001; Zhihua Zhang 004 (CoRR, 2020)

Landscape of Sparse Linear Network: A Brief Investigation. - Dachao Lin; Ruoyu Sun 001; Zhihua Zhang 004 (CoRR, 2020)

Faster Directional Convergence of Linear Neural Networks under Spherically Symmetric Data. - Dachao Lin; Ruoyu Sun 001; Zhihua Zhang 004 (NeurIPS, 2021)

Greedy and Random Quasi-Newton Methods with Faster Explicit Superlinear Convergence. - Dachao Lin; Haishan Ye; Zhihua Zhang 004 (NeurIPS, 2021)

Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent. - Guangzeng Xie; Hao Jin; Dachao Lin; Zhihua Zhang 004 (CoRR, 2021)

Directional Convergence Analysis under Spherically Symmetric Distribution. - Dachao Lin; Zhihua Zhang 004 (CoRR, 2021)

Greedy and Random Broyden's Methods with Explicit Superlinear Convergence Rates in Nonlinear Equations. - Haishan Ye; Dachao Lin; Zhihua Zhang 004 (CoRR, 2021)

On Non-local Convergence Analysis of Deep Linear Networks. - Kun Chen; Dachao Lin; Zhihua Zhang 004 (ICML, 2022)

On the landscape of one-hidden-layer sparse networks and beyond. - Dachao Lin; Ruoyu Sun 001; Zhihua Zhang 004 (Artif. Intell., 2022)

Global Convergence Analysis of Deep Linear Networks with A One-neuron Layer. - Kun Chen; Dachao Lin; Zhihua Zhang 004 (CoRR, 2022)

On the Convergence of Policy in Unregularized Policy Mirror Descent. - Dachao Lin; Zhihua Zhang 004 (CoRR, 2022)

Explicit Convergence Rates of Greedy and Random Quasi-Newton Methods. - Dachao Lin; Haishan Ye; Zhihua Zhang 004 (J. Mach. Learn. Res., 2022)

Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis. - Dachao Lin; Yuze Han; Haishan Ye; Zhihua Zhang 004 (NeurIPS, 2023)

Towards explicit superlinear convergence rate for SR1. - Haishan Ye; Dachao Lin; Xiangyu Chang; Zhihua Zhang 004 (Math. Program., 2023)

LocMoE+: Enhanced Router with Token Feature Awareness for Efficient LLM Pre-Training. - Jing Li; Zhijie Sun; Dachao Lin; Xuan He; Yi Lin; Binfan Zheng; Li Zeng; Rongqian Zhao; Xin Chen (CoRR, 2024)