Dachao Lin

According to our database, Dachao Lin authored at least 19 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

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

2023

Towards explicit superlinear convergence rate for SR1.

Haishan Ye, Dachao Lin, Xiangyu Chang, Zhihua Zhang

Math. Program., May, 2023

Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis.

Dachao Lin, Yuze Han, Haishan Ye, Zhihua Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Explicit Convergence Rates of Greedy and Random Quasi-Newton Methods.

Dachao Lin, Haishan Ye, Zhihua Zhang

J. Mach. Learn. Res., 2022

On the Convergence of Policy in Unregularized Policy Mirror Descent.

Dachao Lin, Zhihua Zhang

CoRR, 2022

Global Convergence Analysis of Deep Linear Networks with A One-neuron Layer.

Kun Chen, Dachao Lin, Zhihua Zhang

CoRR, 2022

On the landscape of one-hidden-layer sparse networks and beyond.

Dachao Lin, Ruoyu Sun, Zhihua Zhang

Artif. Intell., 2022

On Non-local Convergence Analysis of Deep Linear Networks.

Kun Chen, Dachao Lin, Zhihua Zhang

Proceedings of the International Conference on Machine Learning, 2022

2021

Greedy and Random Broyden's Methods with Explicit Superlinear Convergence Rates in Nonlinear Equations.

Haishan Ye, Dachao Lin, Zhihua Zhang

CoRR, 2021

Directional Convergence Analysis under Spherically Symmetric Distribution.

Dachao Lin, Zhihua Zhang

CoRR, 2021

Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent.

Guangzeng Xie, Hao Jin, Dachao Lin, Zhihua Zhang

CoRR, 2021

Greedy and Random Quasi-Newton Methods with Faster Explicit Superlinear Convergence.

Dachao Lin, Haishan Ye, Zhihua Zhang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Faster Directional Convergence of Linear Neural Networks under Spherically Symmetric Data.

Dachao Lin, Ruoyu Sun, Zhihua Zhang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Landscape of Sparse Linear Network: A Brief Investigation.

Dachao Lin, Ruoyu Sun, Zhihua Zhang

CoRR, 2020

Optimal Quantization for Batch Normalization in Neural Network Deployments and Beyond.

Dachao Lin, Peiqin Sun, Guangzeng Xie, Shuchang Zhou, Zhihua Zhang

CoRR, 2020

2019

Towards Understanding the Importance of Noise in Training Neural Networks.

Mo Zhou, Tianyi Liu, Yan Li, Dachao Lin, Enlu Zhou, Tuo Zhao

CoRR, 2019

Towards Better Generalization: BP-SVRG in Training Deep Neural Networks.

Hao Jin, Dachao Lin, Zhihua Zhang

CoRR, 2019

Toward Understanding the Importance of Noise in Training Neural Networks.

Mo Zhou, Tianyi Liu, Yan Li, Dachao Lin, Enlu Zhou, Tuo Zhao

Proceedings of the 36th International Conference on Machine Learning, 2019

2010

Application research of comprehensive evaluation based on the theory of unascertainty measure.

Jinshun Wu, Dachao Lin, Genyin Cheng, Weijie Zhang

Proceedings of the Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 2010