Junhong Lin

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 43

Top Topics

Stochastic Gradient

Distributed Learning

Top Venues

J. Mach. Learn. Res.

IEEE Trans. Circuits Syst. Video Technol.

Publications

Yusu Hong, Junhong Lin
On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions. CoRR (2024)
Hang Xu, Song Li, Junhong Lin
Convergence of projected subgradient method with sparse or low-rank constraints. Adv. Comput. Math. 50 (4) (2024)
Yusu Hong, Junhong Lin
Revisiting Convergence of AdaGrad with Relaxed Assumptions. CoRR (2024)
Tan Sun, Junhong Lin
PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network. CoRR (2024)
Shufan Pei, Junhong Lin, Wenxi Liu, Tiesong Zhao, Chia-Wen Lin
Beyond Night Visibility: Adaptive Multi-Scale Fusion of Infrared and Visible Images. CoRR (2024)
Jing Su, Chufeng Jiang, Xin Jin, Yuxin Qiao, Tingsong Xiao, Hongda Ma, Rong Wei, Zhi Jing, Jiajun Xu, Junhong Lin
Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review. CoRR (2024)
Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, Dawei Zhou, Yada Zhu, Julian Shun
When Heterophily Meets Heterogeneity: New Graph Benchmarks and Effective Methods. CoRR (2024)
Hang Xu, Song Li, Junhong Lin
Nonconvex Deterministic Matrix Completion by Projected Gradient Descent Methods. CoRR (2024)
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
Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography. Bildverarbeitung für die Medizin (2023)
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
Unsupervised detection of small hyperreflective features in ultrahigh resolution optical coherence tomography. CoRR (2023)
Yusu Hong, Junhong Lin
High Probability Convergence of Adam Under Unbounded Gradients and Affine Variance Noise. CoRR (2023)
Junhong Lin, Shufan Pei, Bing Chen, Nanfeng Jiang, Wei Gao, Tiesong Zhao
LDRM: Degradation Rectify Model for Low-light Imaging via Color-Monochrome Cameras. ACM Multimedia (2023)
Nanfeng Jiang, Jiawei Luo, Junhong Lin, Weiling Chen, Tiesong Zhao
Lightweight Semi-supervised Network for Single Image Rain Removal. Pattern Recognit. 137 (2023)
Nanfeng Jiang, Junhong Lin, Ting Zhang, Haifeng Zheng, Tiesong Zhao
Low-Light Image Enhancement via Stage-Transformer-Guided Network. IEEE Trans. Circuits Syst. Video Technol. 33 (8) (2023)
Junhong Lin, Nanfeng Jiang, Zhentao Zhang, Weiling Chen, Tiesong Zhao
LMQFormer: A Laplace-Prior-Guided Mask Query Transformer for Lightweight Snow Removal. IEEE Trans. Circuits Syst. Video Technol. 33 (11) (2023)
Junhong Lin, Nanfeng Jiang, Zhentao Zhang, Weiling Chen, Tiesong Zhao
LMQFormer: A Laplace-Prior-Guided Mask Query Transformer for Lightweight Snow Removal. CoRR (2022)
Ting Zhang, Nanfeng Jiang, Junhong Lin, Jielian Lin, Tiesong Zhao
DesnowFormer: an effective transformer-based image desnowing network. VCIP (2022)
Song Li, Junhong Lin, Dekai Liu, Wenchang Sun
Iterative hard thresholding for compressed data separation. J. Complex. 59 (2020)
Hengjing He, Shangli Zhou, Leping Zhang, Junhong Lin, Weile Chen, Di Wu
Beetle Swarm Optimization Algorithm-Based Load Control with Electricity Storage. J. Control. Sci. Eng. 2020 (2020)
Junhong Lin, Volkan Cevher
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms. J. Mach. Learn. Res. 21 (2020)
Junhong Lin, Volkan Cevher
Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections. J. Mach. Learn. Res. 21 (2020)
Rabeeh Karimi Mahabadi, Junhong Lin, Volkan Cevher
A Learning-Based Framework for Quantized Compressed Sensing. IEEE Signal Process. Lett. 26 (6) (2019)
Junhong Lin, Ding-Xuan Zhou
Online Learning Algorithms Can Converge Comparably Fast as Batch Learning. IEEE Trans. Neural Networks Learn. Syst. 29 (6) (2018)
Junhong Lin, Bang Wang, Guang Yang, Mu Zhou
Indoor Localization Based on Weighted Surfacing from Crowdsourced Samples. Sensors 18 (9) (2018)
Junhong Lin, Volkan Cevher
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods. ICML (2018)
Junhong Lin, Lorenzo Rosasco
Generalization properties of doubly stochastic learning algorithms. J. Complex. 47 (2018)
Junhong Lin, Volkan Cevher
Optimal Rates for Spectral-regularized Algorithms with Least-Squares Regression over Hilbert Spaces. CoRR (2018)
Junhong Lin, Volkan Cevher
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces. ICML (2018)
Junhong Lin, Volkan Cevher
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces. CoRR (2018)
Junhong Lin, Volkan Cevher
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral-Regularization Algorithms. CoRR (2018)
Junhong Lin, Volkan Cevher
Kernel Conjugate Gradient Methods with Random Projections. CoRR (2018)
Junhong Lin, Lorenzo Rosasco, Silvia Villa, Ding-Xuan Zhou
Modified Fejér sequences and applications. Comput. Optim. Appl. 71 (1) (2018)
Junhong Lin, Lorenzo Rosasco
Generalization Properties of Doubly Online Learning Algorithms. CoRR (2017)
Junhong Lin, Lorenzo Rosasco
Optimal Rates for Learning with Nyström Stochastic Gradient Methods. CoRR (2017)
Junhong Lin, Yunwen Lei, Bo Zhang, Ding-Xuan Zhou
Online pairwise learning algorithms with convex loss functions. Inf. Sci. 406 (2017)
Junhong Lin, Lorenzo Rosasco
Optimal Rates for Multi-pass Stochastic Gradient Methods. J. Mach. Learn. Res. 18 (2017)
Junhong Lin, Lorenzo Rosasco
Optimal Learning for Multi-pass Stochastic Gradient Methods. NIPS (2016)
Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco
Generalization Properties and Implicit Regularization for Multiple Passes SGM. ICML (2016)
Junhong Lin, Song Li
Restricted $q$-Isometry Properties Adapted to Frames for Nonconvex $l_q$-Analysis. CoRR (2016)
Junhong Lin, Lorenzo Rosasco
Optimal Learning for Multi-pass Stochastic Gradient Methods. CoRR (2016)
Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco
Generalization Properties and Implicit Regularization for Multiple Passes SGM. CoRR (2016)
Junhong Lin, Lorenzo Rosasco, Ding-Xuan Zhou
Iterative Regularization for Learning with Convex Loss Functions. J. Mach. Learn. Res. 17 (2016)
Junhong Lin, Song Li
-Analysis. IEEE Trans. Inf. Theory 62 (8) (2016)
Junhong Lin, Ding-Xuan Zhou
Learning theory of randomized Kaczmarz algorithm. J. Mach. Learn. Res. 16 (2015)
Junhong Lin, Song Li
Nonuniform support recovery from noisy random measurements by Orthogonal Matching Pursuit. J. Approx. Theory 165 (1) (2013)
Junhong Lin, Song Li, Yi Shen
New Bounds for Restricted Isometry Constants With Coherent Tight Frames. IEEE Trans. Signal Process. 61 (3) (2013)
Junhong Lin, Song Li, Yi Shen
Compressed Data Separation With Redundant Dictionaries. IEEE Trans. Inf. Theory 59 (7) (2013)
Junhong Lin, Song Li
Sparse Recovery with Coherent Tight Frame via Analysis Dantzig Selector and Analysis LASSO CoRR (2013)
Song Li, Junhong Lin
Compressed Sensing with coherent tight frames via $l_q$-minimization for $0<q\leq1$ CoRR (2011)