Lin, Junhong

15 publications

NeurIPS 2025 HeroFilter: Adaptive Spectral Graph Filter for Varying Heterophilic Relations Shuaicheng Zhang, Haohui Wang, Junhong Lin, Xiaojie Guo, Yada Zhu, Si Zhang, Dongqi Fu, Dawei Zhou

ICML 2025 LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection Xinyue Zeng, Haohui Wang, Junhong Lin, Jun Wu, Tyler Cody, Dawei Zhou

ICLR 2025 Reasoning of Large Language Models over Knowledge Graphs with Super-Relations Song Wang, Junhong Lin, Xiaojie Guo, Julian Shun, Jundong Li, Yada Zhu

NeurIPS 2025 Theoretical Investigation of Adafactor for Non-Convex Smooth Optimization Yusu Hong, Junhong Lin

NeurIPS 2024 On Convergence of Adam for Stochastic Optimization Under Relaxed Assumptions Yusu Hong, Junhong Lin

UAI 2024 Revisiting Convergence of AdaGrad with Relaxed Assumptions Yusu Hong, Junhong Lin

JMLR 2020 Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections Junhong Lin, Volkan Cevher

JMLR 2020 Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms Junhong Lin, Volkan Cevher

ICML 2018 Optimal Distributed Learning with Multi-Pass Stochastic Gradient Methods Junhong Lin, Volkan Cevher

ICML 2018 Optimal Rates of Sketched-Regularized Algorithms for Least-Squares Regression over Hilbert Spaces Junhong Lin, Volkan Cevher

JMLR 2017 Optimal Rates for Multi-Pass Stochastic Gradient Methods Junhong Lin, Lorenzo Rosasco

ICML 2016 Generalization Properties and Implicit Regularization for Multiple Passes SGM Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco

JMLR 2016 Iterative Regularization for Learning with Convex Loss Functions Junhong Lin, Lorenzo Rosasco, Ding-Xuan Zhou

NeurIPS 2016 Optimal Learning for Multi-Pass Stochastic Gradient Methods Junhong Lin, Lorenzo Rosasco

JMLR 2015 Learning Theory of Randomized Kaczmarz Algorithm Junhong Lin, Ding-Xuan Zhou