Xinmeng Huang

37 papers A* 13Journal 23Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Convergence-Motivated Learning-to-Optimize Framework for Decentralized Optimization.
IEEE Trans. Signal Process.
Yutong He, Qiulin Shang, Xinmeng Huang, Jialin Liu, Kun Yuan
2025 — conf
D-SOBA: A Single-Loop Decentralized Bilevel Algorithm with Transient Complexity Analysis.
EUSIPCO
Boao Kong, Shuchen Zhu, Songtao Lu, Xinmeng Huang, Kun Yuan
2025 J jnl
Decentralized Bilevel Optimization: A Perspective from Transient Iteration Complexity.
J. Mach. Learn. Res.
Boao Kong, Shuchen Zhu, Songtao Lu, Xinmeng Huang, Kun Yuan
2025 J jnl
Understanding the Influence of Digraphs on Decentralized Optimization: Effective Metrics, Lower Bound, and Optimal Algorithm.
SIAM J. Optim.
Liyuan Liang, Xinmeng Huang, Ran Xin, Kun Yuan
2024 J jnl
Decentralized Bilevel Optimization over Graphs: Loopless Algorithmic Update and Transient Iteration Complexity.
CoRR
Boao Kong, Shuchen Zhu, Songtao Lu, Xinmeng Huang, Kun Yuan
2024 A* conf
Distributed Bilevel Optimization with Communication Compression.
ICML
Yutong He, Jie Hu, Xinmeng Huang, Songtao Lu, Bin Wang, Kun Yuan
2024 A* conf
Momentum Benefits Non-iid Federated Learning Simply and Provably.
ICLR
Ziheng Cheng, Xinmeng Huang, Pengfei Wu, Kun Yuan
2024 A* conf
One-Shot Safety Alignment for Large Language Models via Optimal Dualization.
NeurIPS
Xinmeng Huang, Shuo Li, Edgar Dobriban, Osbert Bastani, Hamed Hassani, Dongsheng Ding
2024 J jnl
One-Shot Safety Alignment for Large Language Models via Optimal Dualization.
CoRR
Xinmeng Huang, Shuo Li, Edgar Dobriban, Osbert Bastani, Hamed Hassani, Dongsheng Ding
2024 A* conf
SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization.
NeurIPS
Shuchen Zhu, Boao Kong, Songtao Lu, Xinmeng Huang, Kun Yuan
2024 J jnl
SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization.
CoRR
Shuchen Zhu, Boao Kong, Songtao Lu, Xinmeng Huang, Kun Yuan
2024 A* conf
Stochastic Controlled Averaging for Federated Learning with Communication Compression.
ICLR
Xinmeng Huang, Ping Li, Xiaoyun Li
2024 A* conf
Uncertainty in Language Models: Assessment through Rank-Calibration.
EMNLP
Xinmeng Huang, Shuo Li, Mengxin Yu, Matteo Sesia, Hamed Hassani, Insup Lee, Osbert Bastani, Edgar Dobriban
2024 J jnl
Uncertainty in Language Models: Assessment through Rank-Calibration.
CoRR
Xinmeng Huang, Shuo Li, Mengxin Yu, Matteo Sesia, Hamed Hassani, Insup Lee, Osbert Bastani, Edgar Dobriban
2023 A* conf
Demystifying Disagreement-on-the-Line in High Dimensions.
ICML
Donghwan Lee, Behrad Moniri, Xinmeng Huang, Edgar Dobriban, Hamed Hassani
2023 J jnl
Demystifying Disagreement-on-the-Line in High Dimensions.
CoRR
Donghwan Lee, Behrad Moniri, Xinmeng Huang, Edgar Dobriban, Hamed Hassani
2023 J jnl
Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression.
CoRR
Yutong He, Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan
2023 J jnl
Momentum Benefits Non-IID Federated Learning Simply and Provably.
CoRR
Ziheng Cheng, Xinmeng Huang, Kun Yuan
2023 J jnl
Optimal Heterogeneous Collaborative Linear Regression and Contextual Bandits.
CoRR
Xinmeng Huang, Kan Xu, Donghwan Lee, Hamed Hassani, Hamsa Bastani, Edgar Dobriban
2023 J jnl
Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD.
J. Mach. Learn. Res.
Kun Yuan, Sulaiman A. Alghunaim, Xinmeng Huang
2023 J jnl
Stochastic Controlled Averaging for Federated Learning with Communication Compression.
CoRR
Xinmeng Huang, Ping Li, Xiaoyun Li
2023 J jnl
T-Cal: An Optimal Test for the Calibration of Predictive Models.
J. Mach. Learn. Res.
Donghwan Lee, Xinmeng Huang, Hamed Hassani, Edgar Dobriban
2023 A* conf
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?
NeurIPS
Yutong He, Xinmeng Huang, Kun Yuan
2023 J jnl
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?
CoRR
Yutong He, Xinmeng Huang, Kun Yuan
2022 A* conf
Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints.
NeurIPS
Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani
2022 J jnl
Collaborative Learning of Distributions under Heterogeneity and Communication Constraints.
CoRR
Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani
2022 A* conf
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression.
NeurIPS
Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan
2022 J jnl
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression.
CoRR
Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan
2022 J jnl
Optimal Complexity in Non-Convex Decentralized Learning over Time-Varying Networks.
CoRR
Xinmeng Huang, Kun Yuan
2022 A* conf
Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization.
NeurIPS
Kun Yuan, Xinmeng Huang, Yiming Chen, Xiaohan Zhang, Yingya Zhang, Pan Pan
2022 J jnl
Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization.
CoRR
Kun Yuan, Xinmeng Huang, Yiming Chen, Xiaohan Zhang, Yingya Zhang, Pan Pan
2022 J jnl
T-Cal: An optimal test for the calibration of predictive models.
CoRR
Donghwan Lee, Xinmeng Huang, Hamed Hassani, Edgar Dobriban
2021 A* conf
An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders.
NeurIPS
Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin
2021 A* conf
DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training.
ICCV
Kun Yuan, Yiming Chen, Xinmeng Huang, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
2021 J jnl
DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training.
CoRR
Kun Yuan, Yiming Chen, Xinmeng Huang, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
2021 J jnl
On the Comparison between Cyclic Sampling and Random Reshuffling.
CoRR
Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin
2020 J jnl
Scaled Relative Graph of Normal Matrices.
CoRR
Xinmeng Huang, Ernest K. Ryu, Wotao Yin