Kun Yuan
57 papers · 2016–2026 · 13 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 12 separate collaboration groups - the largest holds only 39% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Kun Yuan?
6 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Xinmeng Huang, Wotao Yin, Yiming Chen
22 papers
· 2016–2025
· NeurIPS, ICML, JMLR
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A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models
ICML 2025
Decentralized Bilevel Optimization: A Perspective from Transient Iteration Complexity
JMLR 2025
Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures
ICLR 2025
Subspace Optimization for Large Language Models with Convergence Guarantees
ICML 2025
Distributed Bilevel Optimization with Communication Compression
ICML 2024
Momentum Benefits Non-iid Federated Learning Simply and Provably
ICLR 2024
SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization
NeurIPS 2024
AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation
ICML 2023
DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm
ICML 2023
Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD
JMLR 2023
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?
NeurIPS 2023
CHEX: CHannel EXploration for CNN Model Compression
CVPR 2022
Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate
NeurIPS 2022
Effective Model Sparsification by Scheduled Grow-and-Prune Methods
ICLR 2022
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression
NeurIPS 2022
Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization
NeurIPS 2022
Accelerating Gossip SGD with Periodic Global Averaging
ICML 2021
An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders
NeurIPS 2021
DecentLaM: Decentralized Momentum SGD for Large-Batch Deep Training
ICCV 2021
Exponential Graph is Provably Efficient for Decentralized Deep Training
NeurIPS 2021
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
NeurIPS 2019
On the Influence of Momentum Acceleration on Online Learning
JMLR 2016
6 papers whose co-authors appear nowhere else under this name
Distributed Retraction-Free and Communication-Efficient Optimization on the Stiefel Manifold
ICML 2025
HATA: Trainable and Hardware-Efficient Hash-Aware Top-k Attention for Scalable Large Model Inference
ACL 2025
Optimal Complexity in Byzantine-Robust Distributed Stochastic Optimization with Data Heterogeneity
JMLR 2025
Revisiting Gradient Normalization and Clipping for Nonconvex SGD under Heavy-Tailed Noise: Necessity, Sufficiency, and Acceleration
JMLR 2025
Towards Content-Independent Multi-Reference Super-Resolution: Adaptive Pattern Matching and Feature Aggregation
ECCV 2020
SafeNet: Scale-normalization and Anchor-based Feature Extraction Network for Person Re-identification
IJCAI 2018