Junhong Lin

According to our database, Junhong Lin authored at least 47 papers between 2011 and 2025.

Collaborative distances:

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

2025

High probability bounds on AdaGrad for constrained weakly convex optimization.

Yusu Hong, Junhong Lin

J. Complex., 2025

2024

Convergence of projected subgradient method with sparse or low-rank constraints.

Hang Xu, Song Li, Junhong Lin

Adv. Comput. Math., August, 2024

Robust Domain Generalization for Multi-modal Object Recognition.

Yuxin Qiao, Keqin Li, Junhong Lin, Rong Wei, Chufeng Jiang, Yang Luo, Haoyu Yang

CoRR, 2024

When Heterophily Meets Heterogeneity: New Graph Benchmarks and Effective Methods.

Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, Dawei Zhou, Yada Zhu, Julian Shun

CoRR, 2024

Beyond Night Visibility: Adaptive Multi-Scale Fusion of Infrared and Visible Images.

Shufan Pei, Junhong Lin, Wenxi Liu, Tiesong Zhao, Chia-Wen Lin

CoRR, 2024

Revisiting Convergence of AdaGrad with Relaxed Assumptions.

Yusu Hong, Junhong Lin

CoRR, 2024

Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review.

Jing Su, Chufeng Jiang, Xin Jin, Yuxin Qiao, Tingsong Xiao, Hongda Ma, Rong Wei, Zhi Jing, Jiajun Xu, Junhong Lin

CoRR, 2024

PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network.

Tan Sun, Junhong Lin

CoRR, 2024

On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions.

Yusu Hong, Junhong Lin

CoRR, 2024

Nonconvex Deterministic Matrix Completion by Projected Gradient Descent Methods.

Hang Xu, Song Li, Junhong Lin

CoRR, 2024

FraudGT: A Simple, Effective, and Efficient Graph Transformer for Financial Fraud Detection.

Junhong Lin, Xiaojie Guo, Yada Zhu, Samuel Mitchell, Erik Altman, Julian Shun

Proceedings of the 5th ACM International Conference on AI in Finance, 2024

2023

LMQFormer: A Laplace-Prior-Guided Mask Query Transformer for Lightweight Snow Removal.

Junhong Lin, Nanfeng Jiang, Zhentao Zhang, Weiling Chen, Tiesong Zhao

IEEE Trans. Circuits Syst. Video Technol., November, 2023

Low-Light Image Enhancement via Stage-Transformer-Guided Network.

Nanfeng Jiang, Junhong Lin, Ting Zhang, Haifeng Zheng, Tiesong Zhao

IEEE Trans. Circuits Syst. Video Technol., August, 2023

Lightweight Semi-supervised Network for Single Image Rain Removal.

Nanfeng Jiang, Jiawei Luo, Junhong Lin, Weiling Chen, Tiesong Zhao

Pattern Recognit., May, 2023

High Probability Convergence of Adam Under Unbounded Gradients and Affine Variance Noise.

Yusu Hong, Junhong Lin

CoRR, 2023

LDRM: Degradation Rectify Model for Low-light Imaging via Color-Monochrome Cameras.

Junhong Lin, Shufan Pei, Bing Chen, Nanfeng Jiang, Wei Gao, Tiesong Zhao

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography.

Marcel Reimann, Jungeun Won, Hiroyuki Takahashi, Antonio Yaghy, Yunchan Hwang, Stefan B. Ploner, Junhong Lin, Jessica Girgis, Kenneth Lam, Siyu Chen, Nadia K. Waheed, Andreas K. Maier, James G. Fujimoto

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022

DesnowFormer: an effective transformer-based image desnowing network.

Ting Zhang, Nanfeng Jiang, Junhong Lin, Jielian Lin, Tiesong Zhao

Proceedings of the IEEE International Conference on Visual Communications and Image Processing, 2022

2020

Beetle Swarm Optimization Algorithm-Based Load Control with Electricity Storage.

Hengjing He, Shangli Zhou, Leping Zhang, Junhong Lin, Weile Chen, Di Wu

J. Control. Sci. Eng., 2020

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms.

Junhong Lin, Volkan Cevher

J. Mach. Learn. Res., 2020

Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections.

Junhong Lin, Volkan Cevher

J. Mach. Learn. Res., 2020

Iterative hard thresholding for compressed data separation.

Song Li, Junhong Lin, Dekai Liu, Wenchang Sun

J. Complex., 2020

2019

A Learning-Based Framework for Quantized Compressed Sensing.

Rabeeh Karimi Mahabadi, Junhong Lin, Volkan Cevher

IEEE Signal Process. Lett., 2019

2018

Online Learning Algorithms Can Converge Comparably Fast as Batch Learning.

Junhong Lin, Ding-Xuan Zhou

IEEE Trans. Neural Networks Learn. Syst., 2018

Indoor Localization Based on Weighted Surfacing from Crowdsourced Samples.

Junhong Lin, Bang Wang, Guang Yang, Mu Zhou

Sensors, 2018

Generalization properties of doubly stochastic learning algorithms.

Junhong Lin, Lorenzo Rosasco

J. Complex., 2018

Kernel Conjugate Gradient Methods with Random Projections.

Junhong Lin, Volkan Cevher

CoRR, 2018

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral-Regularization Algorithms.

Junhong Lin, Volkan Cevher

CoRR, 2018

Optimal Rates for Spectral-regularized Algorithms with Least-Squares Regression over Hilbert Spaces.

Junhong Lin, Volkan Cevher

CoRR, 2018

Modified Fejér sequences and applications.

Junhong Lin, Lorenzo Rosasco, Silvia Villa, Ding-Xuan Zhou

Comput. Optim. Appl., 2018

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces.

Junhong Lin, Volkan Cevher

Proceedings of the 35th International Conference on Machine Learning, 2018

Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods.

Junhong Lin, Volkan Cevher

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Optimal Rates for Multi-pass Stochastic Gradient Methods.

Junhong Lin, Lorenzo Rosasco

J. Mach. Learn. Res., 2017

Online pairwise learning algorithms with convex loss functions.

Junhong Lin, Yunwen Lei, Bo Zhang, Ding-Xuan Zhou

Inf. Sci., 2017

Optimal Rates for Learning with Nyström Stochastic Gradient Methods.

Junhong Lin, Lorenzo Rosasco

CoRR, 2017

Generalization Properties of Doubly Online Learning Algorithms.

Junhong Lin, Lorenzo Rosasco

CoRR, 2017

2016

Restricted q-Isometry Properties Adapted to Frames for Nonconvex l_q-Analysis.

Junhong Lin, Song Li

IEEE Trans. Inf. Theory, 2016

Iterative Regularization for Learning with Convex Loss Functions.

Junhong Lin, Lorenzo Rosasco, Ding-Xuan Zhou

J. Mach. Learn. Res., 2016

Restricted $q$-Isometry Properties Adapted to Frames for Nonconvex $l_q$-Analysis.

Junhong Lin, Song Li

CoRR, 2016

Optimal Learning for Multi-pass Stochastic Gradient Methods.

Junhong Lin, Lorenzo Rosasco

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Generalization Properties and Implicit Regularization for Multiple Passes SGM.

Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Learning theory of randomized Kaczmarz algorithm.

Junhong Lin, Ding-Xuan Zhou

J. Mach. Learn. Res., 2015

2013

New Bounds for Restricted Isometry Constants With Coherent Tight Frames.

Junhong Lin, Song Li, Yi Shen

IEEE Trans. Signal Process., 2013

Compressed Data Separation With Redundant Dictionaries.

Junhong Lin, Song Li, Yi Shen

IEEE Trans. Inf. Theory, 2013

Nonuniform support recovery from noisy random measurements by Orthogonal Matching Pursuit.

Junhong Lin, Song Li

J. Approx. Theory, 2013

Sparse Recovery with Coherent Tight Frame via Analysis Dantzig Selector and Analysis LASSO

Junhong Lin, Song Li

CoRR, 2013

2011

Compressed Sensing with coherent tight frames via $l_q$-minimization for $0<q\leq1$

Song Li, Junhong Lin

CoRR, 2011