Yunwen Lei - RankMe

115 papers A* 31A 3B 2C 1Journal 74Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Cross-Validation: Adaptive Parameter Selection for Kernel-Based Gradient Descents. CoRR Xiaotong Liu, Yunwen Lei, Xiangyu Chang, Shao-Bo Lin
2026	J	`jnl`	Optimization and Generalization of Gradient Descent for Shallow ReLU Networks with Minimal Width. J. Mach. Learn. Res. Yunwen Lei, Puyu Wang, Yiming Ying, Ding-Xuan Zhou
2026	J	`jnl`	Stochastic Gradient Methods: Bias, Stability and Generalization. J. Mach. Learn. Res. Shuang Zeng, Yunwen Lei
2026	J	`jnl`	Toward Better Generalization Bounds of Stochastic Optimization for Nonconvex Learning. IEEE Trans. Pattern Anal. Mach. Intell. Yunwen Lei
2025	J	`jnl`	Convergence of Adaptive Stochastic Mirror Descent. IEEE Trans. Neural Networks Learn. Syst. Ting Hu, Xiaotong Liu, Kai Ji, Yunwen Lei
2025	A*	`conf`	Generalization Analysis for Deep Contrastive Representation Learning. AAAI Nong Minh Hieu, Antoine Ledent, Yunwen Lei, Cheng Yeaw Ku
2025	J	`jnl`	Generalization Bounds for Rank-sparse Neural Networks. CoRR Antoine Ledent, Rodrigo Alves, Yunwen Lei
2025	J	`jnl`	Generalization Guarantees of Gradient Descent for Shallow Neural Networks. Neural Comput. Puyu Wang, Yunwen Lei, Di Wang, Yiming Ying, Ding-Xuan Zhou
2025	J	`jnl`	Generalization and Optimization of SGD with Lookahead. CoRR Kangcheng Li, Yunwen Lei
2025	A	`conf`	Learning to Sample in Stochastic Optimization. UAI Sijia Zhou, Yunwen Lei, Ata Kabán
2025	A*	`conf`	On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning. ICLR Bokun Wang, Yunwen Lei, Yiming Ying, Tianbao Yang
2025	J	`jnl`	Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification. CoRR Yuanfan Li, Yunwen Lei, Zheng-Chu Guo, Yiming Ying
2025	B	`conf`	Optimal Utility Bounds for Differentially Private Gradient Descent in Three-Layer Neural Networks. DSAA Puyu Wang, Yunwen Lei, Marius Kloft, Yiming Ying
2025	J	`jnl`	PAC-Bayes Guarantees for Data-Adaptive Pairwise Learning. Entropy Sijia Zhou, Yunwen Lei, Ata Kabán
2025	J	`jnl`	Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis. CoRR Sijia Zhou, Yunwen Lei, Ata Kabán
2025	A*	`conf`	Stability and Generalization Analysis of Decentralized SGD: Sharper Bounds Beyond Lipschitzness and Smoothness. ICML Shuang Zeng, Yunwen Lei
2025	A*	`conf`	Stability-based Generalization Analysis of Randomized Coordinate Descent for Pairwise Learning. AAAI Liang Wu, Ruixi Hu, Yunwen Lei
2025	J	`jnl`	Stability-based Generalization Analysis of Randomized Coordinate Descent for Pairwise Learning. CoRR Liang Wu, Ruixi Hu, Yunwen Lei
2024	J	`jnl`	Bootstrap SGD: Algorithmic Stability and Robustness. CoRR Andreas Christmann, Yunwen Lei
2024	J	`jnl`	Differentially private stochastic gradient descent with low-noise. Neurocomputing Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
2024	J	`jnl`	Few-Shot Learning With Dynamic Graph Structure Preserving. IEEE Trans. Ind. Informatics Sichao Fu, Qiong Cao, Yunwen Lei, Yujie Zhong, Yibing Zhan, Xinge You
2024	J	`jnl`	Generalization Analysis for Deep Contrastive Representation Learning. CoRR Nong Minh Hieu, Antoine Ledent, Yunwen Lei, Cheng Yeaw Ku
2024	J	`jnl`	Generalization Bounds with Logarithmic Negative-Sample Dependence for Adversarial Contrastive Learning. Trans. Mach. Learn. Res. Naghmeh Ghanooni, Waleed Mustafa, Yunwen Lei, Anthony Widjaja Lin, Marius Kloft
2024	J	`jnl`	On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning. CoRR Bokun Wang, Yunwen Lei, Yiming Ying, Tianbao Yang
2024	A*	`conf`	Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems. AAAI Jintao Song, Wenqi Lu, Yunwen Lei, Yuchao Tang, Zhenkuan Pan, Jinming Duan
2024	J	`jnl`	Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems. CoRR Jintao Song, Wenqi Lu, Yunwen Lei, Yuchao Tang, Zhenkuan Pan, Jinming Duan
2024	—	`conf`	Self-certified Tuple-Wise Deep Learning. ECML/PKDD (2) Sijia Zhou, Yunwen Lei, Ata Kabán
2023	A*	`conf`	Generalization Analysis for Contrastive Representation Learning. ICML Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou
2023	J	`jnl`	Generalization Analysis for Contrastive Representation Learning. CoRR Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou
2023	A*	`conf`	Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings. AAAI Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft
2023	J	`jnl`	Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks. CoRR Puyu Wang, Yunwen Lei, Di Wang, Yiming Ying, Ding-Xuan Zhou
2023	J	`jnl`	Optimization and Learning With Randomly Compressed Gradient Updates. Neural Comput. Zhanliang Huang, Yunwen Lei, Ata Kabán
2023	J	`jnl`	Pairwise Learning with Adaptive Online Gradient Descent. Trans. Mach. Learn. Res. Tao Sun, Qingsong Wang, Yunwen Lei, Dongsheng Li, Bao Wang
2023	A*	`conf`	Sharper Bounds for Uniformly Stable Algorithms with Stationary Mixing Process. ICLR Shi Fu, Yunwen Lei, Qiong Cao, Xinmei Tian, Dacheng Tao
2023	J	`jnl`	Stability and Generalization for Minibatch SGD and Local SGD. CoRR Yunwen Lei, Tao Sun, Mingrui Liu
2023	A*	`conf`	Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems. COLT Yunwen Lei
2023	A*	`conf`	Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms. NeurIPS Sijia Zhou, Yunwen Lei, Ata Kabán
2022	A*	`conf`	A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks. NeurIPS Mingrui Liu, Zhenxun Zhuang, Yunwen Lei, Chunyang Liao
2022	J	`jnl`	Differentially Private SGDA for Minimax Problems. CoRR Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying
2022	J	`jnl`	Differentially Private Stochastic Gradient Descent with Low-Noise. CoRR Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
2022	A	`conf`	Differentially private SGDA for minimax problems. UAI Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying
2022	J	`jnl`	Early Stopping for Iterative Regularization with General Loss Functions. J. Mach. Learn. Res. Ting Hu, Yunwen Lei
2022	J	`jnl`	Generalization Bounds for Inductive Matrix Completion in Low-noise Settings. CoRR Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft
2022	—	`conf`	Noise-Efficient Learning of Differentially Private Partitioning Machine Ensembles. ECML/PKDD (4) Zhanliang Huang, Yunwen Lei, Ata Kabán
2022	A*	`conf`	On the Generalization Analysis of Adversarial Learning. ICML Waleed Mustafa, Yunwen Lei, Marius Kloft
2022	J	`jnl`	SGFNNs: Signed Graph Filtering-based Neural Networks for Predicting Drug-Drug Interactions. J. Comput. Biol. Ming Chen, Wei Jiang, Yi Pan, Jianhua Dai, Yunwen Lei, Chunyan Ji
2022	A*	`conf`	Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks. NeurIPS Yunwen Lei, Rong Jin, Yiming Ying
2022	J	`jnl`	Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks. CoRR Yunwen Lei, Rong Jin, Yiming Ying
2022	A*	`conf`	Stability and Generalization for Markov Chain Stochastic Gradient Methods. NeurIPS Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
2022	J	`jnl`	Stability and Generalization for Markov Chain Stochastic Gradient Methods. CoRR Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
2022	J	`jnl`	Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems. CoRR Yunwen Lei
2021	J	`jnl`	Differentially Private SGD with Non-Smooth Loss. CoRR Puyu Wang, Yunwen Lei, Yiming Ying, Hai Zhang
2021	J	`jnl`	Differentially private empirical risk minimization for AUC maximization. Neurocomputing Puyu Wang, Zhenhuan Yang, Yunwen Lei, Yiming Ying, Hai Zhang
2021	A*	`conf`	Fine-grained Generalization Analysis of Inductive Matrix Completion. NeurIPS Antoine Ledent, Rodrigo Alves, Yunwen Lei, Marius Kloft
2021	A*	`conf`	Fine-grained Generalization Analysis of Structured Output Prediction. IJCAI Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft
2021	J	`jnl`	Fine-grained Generalization Analysis of Structured Output Prediction. CoRR Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft
2021	A*	`conf`	Fine-grained Generalization Analysis of Vector-Valued Learning. AAAI Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft
2021	J	`jnl`	Fine-grained Generalization Analysis of Vector-valued Learning. CoRR Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft
2021	A*	`conf`	Generalization Guarantee of SGD for Pairwise Learning. NeurIPS Yunwen Lei, Mingrui Liu, Yiming Ying
2021	J	`jnl`	Generalization Performance of Multi-pass Stochastic Gradient Descent with Convex Loss Functions. J. Mach. Learn. Res. Yunwen Lei, Ting Hu, Ke Tang
2021	A*	`conf`	Learning Interpretable Concept Groups in CNNs. IJCAI Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft
2021	J	`jnl`	Learning Interpretable Concept Groups in CNNs. CoRR Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft
2021	J	`jnl`	Learning Rates for Stochastic Gradient Descent With Nonconvex Objectives. IEEE Trans. Pattern Anal. Mach. Intell. Yunwen Lei, Ke Tang
2021	A*	`conf`	Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks. AAAI Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft
2021	A*	`conf`	Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions. ICLR Yunwen Lei, Yiming Ying
2021	A*	`conf`	Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning. NeurIPS Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying
2021	J	`jnl`	Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning. CoRR Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying
2021	A	`conf`	Stability and Differential Privacy of Stochastic Gradient Descent for Pairwise Learning with Non-Smooth Loss. AISTATS Zhenhuan Yang, Yunwen Lei, Siwei Lyu, Yiming Ying
2021	A*	`conf`	Stability and Generalization for Randomized Coordinate Descent. IJCAI Puyu Wang, Liang Wu, Yunwen Lei
2021	J	`jnl`	Stability and Generalization for Randomized Coordinate Descent. CoRR Puyu Wang, Liang Wu, Yunwen Lei
2021	A*	`conf`	Stability and Generalization of Stochastic Gradient Methods for Minimax Problems. ICML Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
2021	J	`jnl`	Stability and Generalization of Stochastic Gradient Methods for Minimax Problems. CoRR Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
2021	J	`jnl`	Stochastic Proximal AUC Maximization. J. Mach. Learn. Res. Yunwen Lei, Yiming Ying
2020	J	`jnl`	Design of a novel low voltage cell lysing instrument. J. Comput. Methods Sci. Eng. Feng Jiang, Mao Li, Yunwen Lei, Jun Yu
2020	A*	`conf`	Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent. ICML Yunwen Lei, Yiming Ying
2020	J	`jnl`	Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent. CoRR Yunwen Lei, Yiming Ying
2020	A*	`conf`	On Performance Estimation in Automatic Algorithm Configuration. AAAI Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao
2020	A*	`conf`	Sharper Generalization Bounds for Pairwise Learning. NeurIPS Yunwen Lei, Antoine Ledent, Marius Kloft
2020	J	`jnl`	Stochastic Gradient Descent for Nonconvex Learning Without Bounded Gradient Assumptions. IEEE Trans. Neural Networks Learn. Syst. Yunwen Lei, Ting Hu, Guiying Li, Ke Tang
2020	A*	`conf`	Stochastic Hard Thresholding Algorithms for AUC Maximization. ICDM Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying
2020	J	`jnl`	Stochastic Hard Thresholding Algorithms for AUC Maximization. CoRR Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying
2019	J	`jnl`	A Generalization Error Bound for Multi-class Domain Generalization. CoRR Aniket Anand Deshmukh, Yunwen Lei, Srinagesh Sharma, Ürün Dogan, James W. Cutler, Clayton Scott
2019	J	`jnl`	Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping. J. Mach. Learn. Res. Shao-Bo Lin, Yunwen Lei, Ding-Xuan Zhou
2019	J	`jnl`	Convergence in Probability on a Big Class of Time-Variant Evolutionary Algorithms. Int. J. Pattern Recognit. Artif. Intell. Ming Chen, Yunwen Lei, Lixin Ding, Zhao Tong
2019	J	`jnl`	Data-Dependent Generalization Bounds for Multi-Class Classification. IEEE Trans. Inf. Theory Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft
2019	J	`jnl`	Improved Generalisation Bounds for Deep Learning Through L CoRR Antoine Ledent, Yunwen Lei, Marius Kloft
2019	J	`jnl`	On Performance Estimation in Automatic Algorithm Configuration. CoRR Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao
2019	A*	`conf`	Optimal Stochastic and Online Learning with Individual Iterates. NeurIPS Yunwen Lei, Peng Yang, Ke Tang, Ding-Xuan Zhou
2019	J	`jnl`	Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions. CoRR Yunwen Lei, Ting Hu, Ke Tang
2019	J	`jnl`	Stochastic Proximal AUC Maximization. CoRR Yunwen Lei, Yiming Ying
2018	B	`conf`	An Enhanced Firefly Algorithm with Orthogonal Centroid Opposition-Based Learning. CEC Lingyun Zhou, Lixin Ding, Yunwen Lei
2018	J	`jnl`	Convergence of Online Mirror Descent Algorithms. CoRR Yunwen Lei, Ding-Xuan Zhou
2018	A*	`conf`	Generalization Bounds for Regularized Pairwise Learning. IJCAI Yunwen Lei, Shao-Bo Lin, Ke Tang
2018	J	`jnl`	Learning Theory of Randomized Sparse Kaczmarz Method. SIAM J. Imaging Sci. Yunwen Lei, Ding-Xuan Zhou
2018	J	`jnl`	Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning. J. Mach. Learn. Res. Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos
2018	J	`jnl`	Refined bounds for online pairwise learning algorithms. Neurocomputing Xiaming Chen, Yunwen Lei
2018	A*	`conf`	Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities. NeurIPS Yunwen Lei, Ke Tang
2017	J	`jnl`	Analysis of Online Composite Mirror Descent Algorithm. Neural Comput. Yunwen Lei, Ding-Xuan Zhou
2017	J	`jnl`	Convergence of Unregularized Online Learning Algorithms. CoRR Yunwen Lei, Lei Shi, Zheng-Chu Guo
2017	J	`jnl`	Convergence of Unregularized Online Learning Algorithms. J. Mach. Learn. Res. Yunwen Lei, Lei Shi, Zheng-Chu Guo
2017	J	`jnl`	Generalization Error Bounds for Extreme Multi-class Classification. CoRR Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft
2017	J	`jnl`	Online pairwise learning algorithms with convex loss functions. Inf. Sci. Junhong Lin, Yunwen Lei, Bo Zhang, Ding-Xuan Zhou
2016	J	`jnl`	Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning. CoRR Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos
2016	J	`jnl`	Local Rademacher complexity bounds based on covering numbers. Neurocomputing Yunwen Lei, Lixin Ding, Yingzhou Bi
2016	C	`conf`	Localized Multiple Kernel Learning - A Convex Approach. ACML Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft
2015	J	`jnl`	Generalization Performance of Radial Basis Function Networks. IEEE Trans. Neural Networks Learn. Syst. Yunwen Lei, Lixin Ding, Wensheng Zhang
2015	J	`jnl`	Local Rademacher Complexity Bounds based on Covering Numbers. CoRR Yunwen Lei, Lixin Ding, Yingzhou Bi
2015	J	`jnl`	Localized Multiple Kernel Learning - A Convex Approach. CoRR Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft
2015	—	`conf`	Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms. NIPS Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft
2015	J	`jnl`	Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms. CoRR Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft
2015	—	`conf`	Theory and Algorithms for the Localized Setting of Learning Kernels. FE@NIPS Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft
2014	J	`jnl`	Generalization ability of fractional polynomial models. Neural Networks Yunwen Lei, Lixin Ding, Yiming Ding
2014	J	`jnl`	Refined Rademacher Chaos Complexity Bounds with Applications to the Multikernel Learning Problem. Neural Comput. Yunwen Lei, Lixin Ding
2013	J	`jnl`	Approximation and estimation bounds for free knot splines. Comput. Math. Appl. Yunwen Lei, Lixin Ding
2013	J	`jnl`	Universal learning using free multivariate splines. Neurocomputing Yunwen Lei, Lixin Ding, Weili Wu