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Junhong Lin

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

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Mar 02, 2024
Shufan Pei, Junhong Lin, Wenxi Liu, Tiesong Zhao, Chia-Wen Lin

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Revisiting Convergence of AdaGrad with Relaxed Assumptions

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Feb 21, 2024
Yusu Hong, Junhong Lin

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

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Feb 15, 2024
Jing Su, Chufeng Jiang, Xin Jin, Yuxin Qiao, Tingsong Xiao, Hongda Ma, Rong Wei, Zhi Jing, Jiajun Xu, Junhong Lin

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On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions

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Feb 06, 2024
Yusu Hong, Junhong Lin

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PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network

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Feb 06, 2024
Tan Sun, Junhong Lin

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

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Nov 03, 2023
Yusu Hong, Junhong Lin

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Unsupervised detection of small hyperreflective features in ultrahigh resolution optical coherence tomography

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Mar 26, 2023
Marcel Reimann, Jungeun Won, Hiroyuki Takahashi, Antonio Yaghy, Yunchan Hwang, Stefan Ploner, Junhong Lin, Jessica Girgis, Kenneth Lam, Siyu Chen, Nadia K. Waheed, Andreas Maier, James G. Fujimoto

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

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Oct 12, 2022
Junhong Lin, Nanfeng Jiang, Zhentao Zhang, Weiling Chen, Tiesong Zhao

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

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Nov 05, 2018
Junhong Lin, Alessandro Rudi, Lorenzo Rosasco, Volkan Cevher

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

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Nov 05, 2018
Junhong Lin, Volkan Cevher

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