Xinmeng Huang

According to our database, Xinmeng Huang authored at least 17 papers between 2020 and 2024.

Collaborative distances:

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

2024

Decentralized Bilevel Optimization over Graphs: Loopless Algorithmic Update and Transient Iteration Complexity.

Boao Kong, Shuchen Zhu, Songtao Lu, Xinmeng Huang, Kun Yuan

CoRR, 2024

2023

Stochastic Controlled Averaging for Federated Learning with Communication Compression.

Xinmeng Huang, Ping Li, Xiaoyun Li

CoRR, 2023

Momentum Benefits Non-IID Federated Learning Simply and Provably.

Ziheng Cheng, Xinmeng Huang, Kun Yuan

CoRR, 2023

Optimal Heterogeneous Collaborative Linear Regression and Contextual Bandits.

Xinmeng Huang, Kan Xu, Donghwan Lee, Hamed Hassani, Hamsa Bastani, Edgar Dobriban

CoRR, 2023

Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression.

Yutong He, Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan

CoRR, 2023

Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?

Yutong He, Xinmeng Huang, Kun Yuan

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

Demystifying Disagreement-on-the-Line in High Dimensions.

Donghwan Lee, Behrad Moniri, Xinmeng Huang, Edgar Dobriban, Hamed Hassani

Proceedings of the International Conference on Machine Learning, 2023

2022

Optimal Complexity in Non-Convex Decentralized Learning over Time-Varying Networks.

Xinmeng Huang, Kun Yuan

CoRR, 2022

Collaborative Learning of Distributions under Heterogeneity and Communication Constraints.

Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani

CoRR, 2022

T-Cal: An optimal test for the calibration of predictive models.

Donghwan Lee, Xinmeng Huang, Hamed Hassani, Edgar Dobriban

CoRR, 2022

Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization.

Kun Yuan, Xinmeng Huang, Yiming Chen, Xiaohan Zhang, Yingya Zhang, Pan Pan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints.

Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression.

Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

On the Comparison between Cyclic Sampling and Random Reshuffling.

Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin

CoRR, 2021

An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders.

Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin

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

DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training.

Kun Yuan, Yiming Chen, Xinmeng Huang, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Scaled Relative Graph of Normal Matrices.

Xinmeng Huang, Ernest K. Ryu, Wotao Yin

CoRR, 2020