Lu, Yucheng

12 publications

NeurIPS 2025 MetaFind: Scene-Aware 3D Asset Retrieval for Coherent Metaverse Scene Generation Zhenyu Pan, Yucheng Lu, Han Liu

ICML 2023 CocktailSGD: Fine-Tuning Foundation Models over 500Mbps Networks Jue Wang, Yucheng Lu, Binhang Yuan, Beidi Chen, Percy Liang, Christopher De Sa, Christopher Re, Ce Zhang

NeurIPS 2023 Coordinating Distributed Example Orders for Provably Accelerated Training A. Feder Cooper, Wentao Guo, Duc Khiem Pham, Tiancheng Yuan, Charlie Ruan, Yucheng Lu, Christopher M De Sa

JMLR 2023 Decentralized Learning: Theoretical Optimality and Practical Improvements Yucheng Lu, Christopher De Sa

ICLR 2023 Maximizing Communication Efficiency for Large-Scale Training via 0/1 Adam Yucheng Lu, Conglong Li, Minjia Zhang, Christopher De Sa, Yuxiong He

ICML 2023 STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition Yucheng Lu, Shivani Agrawal, Suvinay Subramanian, Oleg Rybakov, Christopher De Sa, Amir Yazdanbakhsh

ICLR 2022 A General Analysis of Example-Selection for Stochastic Gradient Descent Yucheng Lu, Si Yi Meng, Christopher De Sa

NeurIPS 2022 GraB: Finding Provably Better Data Permutations than Random Reshuffling Yucheng Lu, Wentao Guo, Christopher M De Sa

NeurIPS 2021 Hyperparameter Optimization Is Deceiving Us, and How to Stop It A. Feder Cooper, Yucheng Lu, Jessica Forde, Christopher M De Sa

ICML 2021 Optimal Complexity in Decentralized Training Yucheng Lu, Christopher De Sa

ICML 2021 Variance Reduced Training with Stratified Sampling for Forecasting Models Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean Foster

ICML 2020 Moniqua: Modulo Quantized Communication in Decentralized SGD Yucheng Lu, Christopher De Sa