Lei, Yunwen

47 publications

AAAI 2025 Generalization Analysis for Deep Contrastive Representation Learning Nong Minh Hieu, Antoine Ledent, Yunwen Lei, Cheng Yeaw Ku

NeurIPS 2025 Generalization Bounds for Rank-Sparse Neural Networks Antoine Ledent, Rodrigo Alves, Yunwen Lei

UAI 2025 Learning to Sample in Stochastic Optimization Sijia Zhou, Yunwen Lei, Ata Kaban

ICLR 2025 On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning Bokun Wang, Yunwen Lei, Yiming Ying, Tianbao Yang

NeurIPS 2025 Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification Yuanfan Li, Yunwen Lei, Zheng-Chu Guo, Yiming Ying

ICML 2025 Stability and Generalization Analysis of Decentralized SGD: Sharper Bounds Beyond Lipschitzness and Smoothness Shuang Zeng, Yunwen Lei

AAAI 2025 Stability-Based Generalization Analysis of Randomized Coordinate Descent for Pairwise Learning Liang Wu, Ruixi Hu, Yunwen Lei

TMLR 2024 Generalization Bounds with Logarithmic Negative-Sample Dependence for Adversarial Contrastive Learning Naghmeh Ghanooni, Waleed Mustafa, Yunwen Lei, Anthony Widjaja Lin, Marius Kloft

NeurIPSW 2024 On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning Bokun Wang, Yunwen Lei, Yiming Ying, Tianbao Yang

AAAI 2024 Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems Jintao Song, Wenqi Lu, Yunwen Lei, Yuchao Tang, Zhenkuan Pan, Jinming Duan

ECML-PKDD 2024 Self-Certified Tuple-Wise Deep Learning Sijia Zhou, Yunwen Lei, Ata Kabán

ICML 2023 Generalization Analysis for Contrastive Representation Learning Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou

AAAI 2023 Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft

TMLR 2023 Pairwise Learning with Adaptive Online Gradient Descent Tao Sun, Qingsong Wang, Yunwen Lei, Dongsheng Li, Bao Wang

ICLR 2023 Sharper Bounds for Uniformly Stable Algorithms with Stationary Mixing Process Shi Fu, Yunwen Lei, Qiong Cao, Xinmei Tian, Dacheng Tao

COLT 2023 Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems Yunwen Lei

NeurIPS 2023 Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms Sijia Zhou, Yunwen Lei, Ata Kaban

NeurIPS 2022 A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks Mingrui Liu, Zhenxun Zhuang, Yunwen Lei, Chunyang Liao

UAI 2022 Differentially Private SGDA for Minimax Problems Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R Vashney, Siwei Lyu, Yiming Ying

JMLR 2022 Early Stopping for Iterative Regularization with General Loss Functions Ting Hu, Yunwen Lei

ECML-PKDD 2022 Noise-Efficient Learning of Differentially Private Partitioning Machine Ensembles Zhanliang Huang, Yunwen Lei, Ata Kabán

ICML 2022 On the Generalization Analysis of Adversarial Learning Waleed Mustafa, Yunwen Lei, Marius Kloft

NeurIPS 2022 Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks Yunwen Lei, Rong Jin, Yiming Ying

NeurIPS 2022 Stability and Generalization for Markov Chain Stochastic Gradient Methods Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou

AISTATS 2021 Stability and Differential Privacy of Stochastic Gradient Descent for Pairwise Learning with Non-Smooth Loss Zhenhuan Yang, Yunwen Lei, Siwei Lyu, Yiming Ying

NeurIPS 2021 Fine-Grained Generalization Analysis of Inductive Matrix Completion Antoine Ledent, Rodrigo Alves, Yunwen Lei, Marius Kloft

IJCAI 2021 Fine-Grained Generalization Analysis of Structured Output Prediction Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft

AAAI 2021 Fine-Grained Generalization Analysis of Vector-Valued Learning Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft

NeurIPS 2021 Generalization Guarantee of SGD for Pairwise Learning Yunwen Lei, Mingrui Liu, Yiming Ying

JMLR 2021 Generalization Performance of Multi-Pass Stochastic Gradient Descent with Convex Loss Functions Yunwen Lei, Ting Hu, Ke Tang

IJCAI 2021 Learning Interpretable Concept Groups in CNNs Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft

AAAI 2021 Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft

ICLR 2021 Sharper Generalization Bounds for Learning with Gradient-Dominated Objective Functions Yunwen Lei, Yiming Ying

NeurIPS 2021 Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying

IJCAI 2021 Stability and Generalization for Randomized Coordinate Descent Puyu Wang, Liang Wu, Yunwen Lei

ICML 2021 Stability and Generalization of Stochastic Gradient Methods for Minimax Problems Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying

JMLR 2021 Stochastic Proximal AUC Maximization Yunwen Lei, Yiming Ying

ICML 2020 Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent Yunwen Lei, Yiming Ying

AAAI 2020 On Performance Estimation in Automatic Algorithm Configuration Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao

NeurIPS 2020 Sharper Generalization Bounds for Pairwise Learning Yunwen Lei, Antoine Ledent, Marius Kloft

JMLR 2019 Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping Shao-Bo Lin, Yunwen Lei, Ding-Xuan Zhou

NeurIPS 2019 Optimal Stochastic and Online Learning with Individual Iterates Yunwen Lei, Peng Yang, Ke Tang, Ding-Xuan Zhou

IJCAI 2018 Generalization Bounds for Regularized Pairwise Learning Yunwen Lei, Shao-Bo Lin, Ke Tang

JMLR 2018 Local Rademacher Complexity-Based Learning Guarantees for Multi-Task Learning Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos

NeurIPS 2018 Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities Yunwen Lei, Ke Tang

ACML 2016 Localized Multiple Kernel Learning—A Convex Approach Yunwen Lei, Alexander Binder, Urun Dogan, Marius Kloft

NeurIPS 2015 Multi-Class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms Yunwen Lei, Urun Dogan, Alexander Binder, Marius Kloft