Yucheng Lu

22 papers A* 10Journal 12
YearRankTypeTitle / Venue / Authors
2023 A* conf
CD-GraB: Coordinating Distributed Example Orders for Provably Accelerated Training.
NeurIPS
A. Feder Cooper, Wentao Guo, Khiem Pham, Tiancheng Yuan, Charlie Ruan, Yucheng Lu, Christopher De Sa
2023 A* conf
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks.
ICML
Jue Wang, Yucheng Lu, Binhang Yuan, Beidi Chen, Percy Liang, Christopher De Sa, Christopher Ré, Ce Zhang
2023 J jnl
Decentralized Learning: Theoretical Optimality and Practical Improvements.
J. Mach. Learn. Res.
Yucheng Lu, Christopher De Sa
2023 A* conf
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam.
ICLR
Yucheng Lu, Conglong Li, Minjia Zhang, Christopher De Sa, Yuxiong He
2023 A* conf
STEP: Learning N: M Structured Sparsity Masks from Scratch with Precondition.
ICML
Yucheng Lu, Shivani Agrawal, Suvinay Subramanian, Oleg Rybakov, Christopher De Sa, Amir Yazdanbakhsh
2023 J jnl
STEP: Learning N: M Structured Sparsity Masks from Scratch with Precondition.
CoRR
Yucheng Lu, Shivani Agrawal, Suvinay Subramanian, Oleg Rybakov, Christopher De Sa, Amir Yazdanbakhsh
2023 J jnl
Scale up with Order: Finding Good Data Permutations for Distributed Training.
CoRR
Wentao Guo, Khiem Pham, Yucheng Lu, Tiancheng Yuan, Charlie F. Ruan, Christopher De Sa
2022 A* conf
A General Analysis of Example-Selection for Stochastic Gradient Descent.
ICLR
Yucheng Lu, Si Yi Meng, Christopher De Sa
2022 A* conf
GraB: Finding Provably Better Data Permutations than Random Reshuffling.
NeurIPS
Yucheng Lu, Wentao Guo, Christopher De Sa
2022 J jnl
GraB: Finding Provably Better Data Permutations than Random Reshuffling.
CoRR
Yucheng Lu, Wentao Guo, Christopher De Sa
2022 J jnl
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam.
CoRR
Yucheng Lu, Conglong Li, Minjia Zhang, Christopher De Sa, Yuxiong He
2021 J jnl
Adaptive Diffusion of Sensitive Information in Online Social Networks.
IEEE Trans. Knowl. Data Eng.
Xudong Wu, Luoyi Fu, Huan Long, Dali Yang, Yucheng Lu, Xinbing Wang, Guihai Chen
2021 A* conf
Hyperparameter Optimization Is Deceiving Us, and How to Stop It.
NeurIPS
A. Feder Cooper, Yucheng Lu, Jessica Forde, Christopher De Sa
2021 J jnl
Hyperparameter Optimization Is Deceiving Us, and How to Stop It.
CoRR
A. Feder Cooper, Yucheng Lu, Christopher De Sa
2021 A* conf
Optimal Complexity in Decentralized Training.
ICML
Yucheng Lu, Christopher De Sa
2021 A* conf
Variance Reduced Training with Stratified Sampling for Forecasting Models.
ICML
Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean P. Foster
2021 J jnl
Variance Reduction in Training Forecasting Models with Subgroup Sampling.
CoRR
Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean P. Foster
2020 J jnl
MixML: A Unified Analysis of Weakly Consistent Parallel Learning.
CoRR
Yucheng Lu, Jack Nash, Christopher De Sa
2020 A* conf
Moniqua: Modulo Quantized Communication in Decentralized SGD.
ICML
Yucheng Lu, Christopher De Sa
2020 J jnl
Moniqua: Modulo Quantized Communication in Decentralized SGD.
CoRR
Yucheng Lu, Christopher De Sa
2020 J jnl
Towards Optimal Convergence Rate in Decentralized Stochastic Training.
CoRR
Yucheng Lu, Zheng Li, Christopher De Sa
2018 J jnl
BLAG: Bandit On Large Action Set Graph.
CoRR
Yucheng Lu, Xudong Wu, Jingfan Meng, Luoyi Fu, Xinbing Wang