Yunwen Lei

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 83

Top Topics

Generalization Bounds

Stochastic Gradient

Top Venues

J. Mach. Learn. Res.

Publications

Sichao Fu, Qiong Cao, Yunwen Lei, Yujie Zhong, Yibing Zhan, Xinge You
Few-Shot Learning With Dynamic Graph Structure Preserving. IEEE Trans. Ind. Informatics 20 (3) (2024)
Jintao Song, Wenqi Lu, Yunwen Lei, Yuchao Tang, Zhenkuan Pan, Jinming Duan
Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems. AAAI (2024)
Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
Differentially private stochastic gradient descent with low-noise. Neurocomputing 585 (2024)
Jintao Song, Wenqi Lu, Yunwen Lei, Yuchao Tang, Zhenkuan Pan, Jinming Duan
Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems. CoRR (2024)
Sijia Zhou, Yunwen Lei, Ata Kabán
Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms. NeurIPS (2023)
Yunwen Lei
Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems. COLT (2023)
Puyu Wang, Yunwen Lei, Di Wang, Yiming Ying, Ding-Xuan Zhou
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks. CoRR (2023)
Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou
Generalization Analysis for Contrastive Representation Learning. CoRR (2023)
Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft
Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings. AAAI (2023)
Tao Sun, Qingsong Wang, Yunwen Lei, Dongsheng Li, Bao Wang
Pairwise Learning with Adaptive Online Gradient Descent. Trans. Mach. Learn. Res. 2023 (2023)
Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou
Generalization Analysis for Contrastive Representation Learning. ICML (2023)
Zhanliang Huang, Yunwen Lei, Ata Kabán
Optimization and Learning With Randomly Compressed Gradient Updates. Neural Comput. 35 (7) (2023)
Yunwen Lei, Tao Sun, Mingrui Liu
Stability and Generalization for Minibatch SGD and Local SGD. CoRR (2023)
Shi Fu, Yunwen Lei, Qiong Cao, Xinmei Tian, Dacheng Tao
Sharper Bounds for Uniformly Stable Algorithms with Stationary Mixing Process. ICLR (2023)
Zhanliang Huang, Yunwen Lei, Ata Kabán
Noise-Efficient Learning of Differentially Private Partitioning Machine Ensembles. ECML/PKDD (4) (2022)
Ming Chen, Wei Jiang, Yi Pan, Jianhua Dai, Yunwen Lei, Chunyan Ji
SGFNNs: Signed Graph Filtering-based Neural Networks for Predicting Drug-Drug Interactions. J. Comput. Biol. 29 (10) (2022)
Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft
Generalization Bounds for Inductive Matrix Completion in Low-noise Settings. CoRR (2022)
Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
Stability and Generalization for Markov Chain Stochastic Gradient Methods. NeurIPS (2022)
Meng Ding, Mingxi Lei, Yunwen Lei, Di Wang, Jinhui Xu
On Stability and Generalization of Bilevel Optimization Problem. CoRR (2022)
Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying
Differentially Private SGDA for Minimax Problems. CoRR (2022)
Waleed Mustafa, Yunwen Lei, Marius Kloft
On the Generalization Analysis of Adversarial Learning. ICML (2022)
Yunwen Lei, Rong Jin, Yiming Ying
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks. CoRR (2022)
Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying
Differentially private SGDA for minimax problems. UAI (2022)
Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
Stability and Generalization for Markov Chain Stochastic Gradient Methods. CoRR (2022)
Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
Differentially Private Stochastic Gradient Descent with Low-Noise. CoRR (2022)
Mingrui Liu, Zhenxun Zhuang, Yunwen Lei, Chunyang Liao
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks. NeurIPS (2022)
Yunwen Lei
Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems. CoRR (2022)
Yunwen Lei, Rong Jin, Yiming Ying
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks. NeurIPS (2022)
Ting Hu, Yunwen Lei
Early Stopping for Iterative Regularization with General Loss Functions. J. Mach. Learn. Res. 23 (2022)
Puyu Wang, Yunwen Lei, Yiming Ying, Hai Zhang
Differentially Private SGD with Non-Smooth Loss. CoRR (2021)
Yunwen Lei, Ting Hu, Ke Tang
Generalization Performance of Multi-pass Stochastic Gradient Descent with Convex Loss Functions. J. Mach. Learn. Res. 22 (2021)
Yunwen Lei, Ke Tang
Learning Rates for Stochastic Gradient Descent With Nonconvex Objectives. IEEE Trans. Pattern Anal. Mach. Intell. 43 (12) (2021)
Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft
Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks. AAAI (2021)
Yunwen Lei, Mingrui Liu, Yiming Ying
Generalization Guarantee of SGD for Pairwise Learning. NeurIPS (2021)
Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft
Learning Interpretable Concept Groups in CNNs. CoRR (2021)
Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft
Learning Interpretable Concept Groups in CNNs. IJCAI (2021)
Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft
Fine-grained Generalization Analysis of Structured Output Prediction. CoRR (2021)
Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft
Fine-grained Generalization Analysis of Vector-Valued Learning. AAAI (2021)
Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning. CoRR (2021)
Yunwen Lei, Yiming Ying
Stochastic Proximal AUC Maximization. J. Mach. Learn. Res. 22 (2021)
Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft
Fine-grained Generalization Analysis of Vector-valued Learning. CoRR (2021)
Puyu Wang, Liang Wu, Yunwen Lei
Stability and Generalization for Randomized Coordinate Descent. CoRR (2021)
Yunwen Lei, Yiming Ying
Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions. ICLR (2021)
Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems. CoRR (2021)
Antoine Ledent, Rodrigo Alves, Yunwen Lei, Marius Kloft
Fine-grained Generalization Analysis of Inductive Matrix Completion. NeurIPS (2021)
Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems. ICML (2021)
Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning. NeurIPS (2021)
Zhenhuan Yang, Yunwen Lei, Siwei Lyu, Yiming Ying
Stability and Differential Privacy of Stochastic Gradient Descent for Pairwise Learning with Non-Smooth Loss. AISTATS (2021)
Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft
Fine-grained Generalization Analysis of Structured Output Prediction. IJCAI (2021)
Puyu Wang, Liang Wu, Yunwen Lei
Stability and Generalization for Randomized Coordinate Descent. IJCAI (2021)
Puyu Wang, Zhenhuan Yang, Yunwen Lei, Yiming Ying, Hai Zhang
Differentially private empirical risk minimization for AUC maximization. Neurocomputing 461 (2021)
Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying
Stochastic Hard Thresholding Algorithms for AUC Maximization. CoRR (2020)
Yunwen Lei, Ting Hu, Guiying Li, Ke Tang
Stochastic Gradient Descent for Nonconvex Learning Without Bounded Gradient Assumptions. IEEE Trans. Neural Networks Learn. Syst. 31 (10) (2020)
Yunwen Lei, Yiming Ying
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent. ICML (2020)
Yunwen Lei, Antoine Ledent, Marius Kloft
Sharper Generalization Bounds for Pairwise Learning. NeurIPS (2020)
Yunwen Lei, Yiming Ying
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent. CoRR (2020)
Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao
On Performance Estimation in Automatic Algorithm Configuration. AAAI (2020)
Feng Jiang, Mao Li, Yunwen Lei, Jun Yu
Design of a novel low voltage cell lysing instrument. J. Comput. Methods Sci. Eng. 20 (1) (2020)
Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying
Stochastic Hard Thresholding Algorithms for AUC Maximization. ICDM (2020)
Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft
Data-Dependent Generalization Bounds for Multi-Class Classification. IEEE Trans. Inf. Theory 65 (5) (2019)
Yunwen Lei, Ting Hu, Ke Tang
Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions. CoRR (2019)
Ming Chen, Yunwen Lei, Lixin Ding, Zhao Tong
Convergence in Probability on a Big Class of Time-Variant Evolutionary Algorithms. Int. J. Pattern Recognit. Artif. Intell. 33 (6) (2019)
Yunwen Lei, Yiming Ying
Stochastic Proximal AUC Maximization. CoRR (2019)
Antoine Ledent, Yunwen Lei, Marius Kloft
Covering Numbers. CoRR (2019)
Shao-Bo Lin, Yunwen Lei, Ding-Xuan Zhou
Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping. J. Mach. Learn. Res. 20 (2019)
Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao
On Performance Estimation in Automatic Algorithm Configuration. CoRR (2019)
Yunwen Lei, Peng Yang, Ke Tang, Ding-Xuan Zhou
Optimal Stochastic and Online Learning with Individual Iterates. NeurIPS (2019)
Aniket Anand Deshmukh, Yunwen Lei, Srinagesh Sharma, Ürün Dogan, James W. Cutler, Clayton Scott
A Generalization Error Bound for Multi-class Domain Generalization. CoRR (2019)
Lingyun Zhou, Lixin Ding, Yunwen Lei
An Enhanced Firefly Algorithm with Orthogonal Centroid Opposition-Based Learning. CEC (2018)
Yunwen Lei, Shao-Bo Lin, Ke Tang
Generalization Bounds for Regularized Pairwise Learning. IJCAI (2018)
Yunwen Lei, Ding-Xuan Zhou
Learning Theory of Randomized Sparse Kaczmarz Method. SIAM J. Imaging Sci. 11 (1) (2018)
Yunwen Lei, Ding-Xuan Zhou
Convergence of Online Mirror Descent Algorithms. CoRR (2018)
Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos
Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning. J. Mach. Learn. Res. 19 (2018)
Xiaming Chen, Yunwen Lei
Refined bounds for online pairwise learning algorithms. Neurocomputing 275 (2018)
Yunwen Lei, Ke Tang
Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities. NeurIPS (2018)
Yunwen Lei, Lei Shi, Zheng-Chu Guo
Convergence of Unregularized Online Learning Algorithms. CoRR (2017)
Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft
Generalization Error Bounds for Extreme Multi-class Classification. CoRR (2017)
Yunwen Lei, Ding-Xuan Zhou
Analysis of Online Composite Mirror Descent Algorithm. Neural Comput. 29 (3) (2017)
Yunwen Lei, Lei Shi, Zheng-Chu Guo
Convergence of Unregularized Online Learning Algorithms. J. Mach. Learn. Res. 18 (2017)
Junhong Lin, Yunwen Lei, Bo Zhang, Ding-Xuan Zhou
Online pairwise learning algorithms with convex loss functions. Inf. Sci. 406 (2017)
Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft
Localized Multiple Kernel Learning - A Convex Approach. ACML (2016)
Yunwen Lei, Lixin Ding, Yingzhou Bi
Local Rademacher complexity bounds based on covering numbers. Neurocomputing 218 (2016)
Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos
Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning. CoRR (2016)
Yunwen Lei, Lixin Ding, Yingzhou Bi
Local Rademacher Complexity Bounds based on Covering Numbers. CoRR (2015)
Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft
Localized Multiple Kernel Learning - A Convex Approach. CoRR (2015)
Yunwen Lei, Lixin Ding, Wensheng Zhang
Generalization Performance of Radial Basis Function Networks. IEEE Trans. Neural Networks Learn. Syst. 26 (3) (2015)
Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft
Theory and Algorithms for the Localized Setting of Learning Kernels. FE@NIPS (2015)
Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms. NIPS (2015)
Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms. CoRR (2015)
Yunwen Lei, Lixin Ding, Yiming Ding
Generalization ability of fractional polynomial models. Neural Networks 49 (2014)
Yunwen Lei, Lixin Ding
Refined Rademacher Chaos Complexity Bounds with Applications to the Multikernel Learning Problem. Neural Comput. 26 (4) (2014)
Yunwen Lei, Lixin Ding, Weili Wu
Universal learning using free multivariate splines. Neurocomputing 119 (2013)
Yunwen Lei, Lixin Ding
Approximation and estimation bounds for free knot splines. Comput. Math. Appl. 65 (7) (2013)