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Yunwen Lei
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2020 – today
- 2024
- [j27]Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou:
Differentially private stochastic gradient descent with low-noise. Neurocomputing 585: 127557 (2024) - [j26]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): 3306-3315 (2024) - [c35]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: 8117-8125 - [c34]Sijia Zhou, Yunwen Lei, Ata Kabán:
Self-certified Tuple-Wise Deep Learning. ECML/PKDD (2) 2024: 303-320 - [i31]Jintao Song, Wenqi Lu, Yunwen Lei, Yuchao Tang, Zhenkuan Pan, Jinming Duan:
Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems. CoRR abs/2401.00657 (2024) - 2023
- [j25]Zhanliang Huang, Yunwen Lei, Ata Kabán:
Optimization and Learning With Randomly Compressed Gradient Updates. Neural Comput. 35(7): 1234-1287 (2023) - [j24]Tao Sun, Qingsong Wang, Yunwen Lei, Dongsheng Li, Bao Wang:
Pairwise Learning with Adaptive Online Gradient Descent. Trans. Mach. Learn. Res. 2023 (2023) - [c33]Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft:
Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings. AAAI 2023: 8447-8455 - [c32]Yunwen Lei:
Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems. COLT 2023: 191-227 - [c31]Shi Fu, Yunwen Lei, Qiong Cao, Xinmei Tian, Dacheng Tao:
Sharper Bounds for Uniformly Stable Algorithms with Stationary Mixing Process. ICLR 2023 - [c30]Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou:
Generalization Analysis for Contrastive Representation Learning. ICML 2023: 19200-19227 - [c29]Sijia Zhou, Yunwen Lei, Ata Kabán:
Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms. NeurIPS 2023 - [i30]Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou:
Generalization Analysis for Contrastive Representation Learning. CoRR abs/2302.12383 (2023) - [i29]Puyu Wang, Yunwen Lei, Di Wang, Yiming Ying, Ding-Xuan Zhou:
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks. CoRR abs/2305.16891 (2023) - [i28]Yunwen Lei, Tao Sun, Mingrui Liu:
Stability and Generalization for Minibatch SGD and Local SGD. CoRR abs/2310.01139 (2023) - 2022
- [j23]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): 1104-1116 (2022) - [j22]Ting Hu, Yunwen Lei:
Early Stopping for Iterative Regularization with General Loss Functions. J. Mach. Learn. Res. 23: 339:1-339:36 (2022) - [c28]Waleed Mustafa, Yunwen Lei, Marius Kloft:
On the Generalization Analysis of Adversarial Learning. ICML 2022: 16174-16196 - [c27]Yunwen Lei, Rong Jin, Yiming Ying:
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks. NeurIPS 2022 - [c26]Mingrui Liu, Zhenxun Zhuang, Yunwen Lei, Chunyang Liao:
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks. NeurIPS 2022 - [c25]Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou:
Stability and Generalization for Markov Chain Stochastic Gradient Methods. NeurIPS 2022 - [c24]Zhanliang Huang, Yunwen Lei, Ata Kabán:
Noise-Efficient Learning of Differentially Private Partitioning Machine Ensembles. ECML/PKDD (4) 2022: 587-603 - [c23]Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying:
Differentially private SGDA for minimax problems. UAI 2022: 2192-2202 - [i27]Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying:
Differentially Private SGDA for Minimax Problems. CoRR abs/2201.09046 (2022) - [i26]Yunwen Lei:
Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems. CoRR abs/2206.07082 (2022) - [i25]Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou:
Differentially Private Stochastic Gradient Descent with Low-Noise. CoRR abs/2209.04188 (2022) - [i24]Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou:
Stability and Generalization for Markov Chain Stochastic Gradient Methods. CoRR abs/2209.08005 (2022) - [i23]Yunwen Lei, Rong Jin, Yiming Ying:
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks. CoRR abs/2209.09298 (2022) - [i22]Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft:
Generalization Bounds for Inductive Matrix Completion in Low-noise Settings. CoRR abs/2212.08339 (2022) - 2021
- [j21]Puyu Wang, Zhenhuan Yang, Yunwen Lei, Yiming Ying, Hai Zhang:
Differentially private empirical risk minimization for AUC maximization. Neurocomputing 461: 419-437 (2021) - [j20]Yunwen Lei, Ting Hu, Ke Tang:
Generalization Performance of Multi-pass Stochastic Gradient Descent with Convex Loss Functions. J. Mach. Learn. Res. 22: 25:1-25:41 (2021) - [j19]Yunwen Lei, Yiming Ying:
Stochastic Proximal AUC Maximization. J. Mach. Learn. Res. 22: 61:1-61:45 (2021) - [j18]Yunwen Lei, Ke Tang:
Learning Rates for Stochastic Gradient Descent With Nonconvex Objectives. IEEE Trans. Pattern Anal. Mach. Intell. 43(12): 4505-4511 (2021) - [c22]Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft:
Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks. AAAI 2021: 8279-8287 - [c21]Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft:
Fine-grained Generalization Analysis of Vector-Valued Learning. AAAI 2021: 10338-10346 - [c20]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: 2026-2034 - [c19]Yunwen Lei, Yiming Ying:
Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions. ICLR 2021 - [c18]Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying:
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems. ICML 2021: 6175-6186 - [c17]Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft:
Learning Interpretable Concept Groups in CNNs. IJCAI 2021: 1061-1067 - [c16]Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft:
Fine-grained Generalization Analysis of Structured Output Prediction. IJCAI 2021: 2841-2847 - [c15]Puyu Wang, Liang Wu, Yunwen Lei:
Stability and Generalization for Randomized Coordinate Descent. IJCAI 2021: 3104-3110 - [c14]Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying:
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning. NeurIPS 2021: 20160-20171 - [c13]Yunwen Lei, Mingrui Liu, Yiming Ying:
Generalization Guarantee of SGD for Pairwise Learning. NeurIPS 2021: 21216-21228 - [c12]Antoine Ledent, Rodrigo Alves, Yunwen Lei, Marius Kloft:
Fine-grained Generalization Analysis of Inductive Matrix Completion. NeurIPS 2021: 25540-25552 - [i21]Puyu Wang, Yunwen Lei, Yiming Ying, Hai Zhang:
Differentially Private SGD with Non-Smooth Loss. CoRR abs/2101.08925 (2021) - [i20]Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft:
Fine-grained Generalization Analysis of Vector-valued Learning. CoRR abs/2104.14173 (2021) - [i19]Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying:
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems. CoRR abs/2105.03793 (2021) - [i18]Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft:
Fine-grained Generalization Analysis of Structured Output Prediction. CoRR abs/2106.00115 (2021) - [i17]Puyu Wang, Liang Wu, Yunwen Lei:
Stability and Generalization for Randomized Coordinate Descent. CoRR abs/2108.07414 (2021) - [i16]Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft:
Learning Interpretable Concept Groups in CNNs. CoRR abs/2109.10078 (2021) - [i15]Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying:
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning. CoRR abs/2111.12050 (2021) - 2020
- [j17]Feng Jiang, Mao Li, Yunwen Lei, Jun Yu:
Design of a novel low voltage cell lysing instrument. J. Comput. Methods Sci. Eng. 20(1): 101-111 (2020) - [j16]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): 4394-4400 (2020) - [c11]Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao:
On Performance Estimation in Automatic Algorithm Configuration. AAAI 2020: 2384-2391 - [c10]Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying:
Stochastic Hard Thresholding Algorithms for AUC Maximization. ICDM 2020: 741-750 - [c9]Yunwen Lei, Yiming Ying:
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent. ICML 2020: 5809-5819 - [c8]Yunwen Lei, Antoine Ledent, Marius Kloft:
Sharper Generalization Bounds for Pairwise Learning. NeurIPS 2020 - [i14]Yunwen Lei, Yiming Ying:
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent. CoRR abs/2006.08157 (2020) - [i13]Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying:
Stochastic Hard Thresholding Algorithms for AUC Maximization. CoRR abs/2011.02396 (2020)
2010 – 2019
- 2019
- [j15]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): 1959018:1-1959018:34 (2019) - [j14]Shao-Bo Lin, Yunwen Lei, Ding-Xuan Zhou:
Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping. J. Mach. Learn. Res. 20: 46:1-46:36 (2019) - [j13]Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft:
Data-Dependent Generalization Bounds for Multi-Class Classification. IEEE Trans. Inf. Theory 65(5): 2995-3021 (2019) - [c7]Yunwen Lei, Peng Yang, Ke Tang, Ding-Xuan Zhou:
Optimal Stochastic and Online Learning with Individual Iterates. NeurIPS 2019: 5416-5426 - [i12]Yunwen Lei, Ting Hu, Ke Tang:
Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions. CoRR abs/1902.00908 (2019) - [i11]Aniket Anand Deshmukh, Yunwen Lei, Srinagesh Sharma, Ürün Dogan, James W. Cutler, Clayton Scott:
A Generalization Error Bound for Multi-class Domain Generalization. CoRR abs/1905.10392 (2019) - [i10]Antoine Ledent, Yunwen Lei, Marius Kloft:
Improved Generalisation Bounds for Deep Learning Through L∞ Covering Numbers. CoRR abs/1905.12430 (2019) - [i9]Yunwen Lei, Yiming Ying:
Stochastic Proximal AUC Maximization. CoRR abs/1906.06053 (2019) - [i8]Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao:
On Performance Estimation in Automatic Algorithm Configuration. CoRR abs/1911.08200 (2019) - 2018
- [j12]Xiaming Chen, Yunwen Lei:
Refined bounds for online pairwise learning algorithms. Neurocomputing 275: 2656-2665 (2018) - [j11]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: 38:1-38:47 (2018) - [j10]Yunwen Lei, Ding-Xuan Zhou:
Learning Theory of Randomized Sparse Kaczmarz Method. SIAM J. Imaging Sci. 11(1): 547-574 (2018) - [c6]Lingyun Zhou, Lixin Ding, Yunwen Lei:
An Enhanced Firefly Algorithm with Orthogonal Centroid Opposition-Based Learning. CEC 2018: 1-8 - [c5]Yunwen Lei, Shao-Bo Lin, Ke Tang:
Generalization Bounds for Regularized Pairwise Learning. IJCAI 2018: 2376-2382 - [c4]Yunwen Lei, Ke Tang:
Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities. NeurIPS 2018: 1526-1536 - [i7]Yunwen Lei, Ding-Xuan Zhou:
Convergence of Online Mirror Descent Algorithms. CoRR abs/1802.06357 (2018) - 2017
- [j9]Junhong Lin, Yunwen Lei, Bo Zhang, Ding-Xuan Zhou:
Online pairwise learning algorithms with convex loss functions. Inf. Sci. 406: 57-70 (2017) - [j8]Yunwen Lei, Lei Shi, Zheng-Chu Guo:
Convergence of Unregularized Online Learning Algorithms. J. Mach. Learn. Res. 18: 171:1-171:33 (2017) - [j7]Yunwen Lei, Ding-Xuan Zhou:
Analysis of Online Composite Mirror Descent Algorithm. Neural Comput. 29(3): 825-860 (2017) - [i6]Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft:
Generalization Error Bounds for Extreme Multi-class Classification. CoRR abs/1706.09814 (2017) - [i5]Yunwen Lei, Lei Shi, Zheng-Chu Guo:
Convergence of Unregularized Online Learning Algorithms. CoRR abs/1708.02939 (2017) - 2016
- [j6]Yunwen Lei, Lixin Ding, Yingzhou Bi:
Local Rademacher complexity bounds based on covering numbers. Neurocomputing 218: 320-330 (2016) - [c3]Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft:
Localized Multiple Kernel Learning - A Convex Approach. ACML 2016: 81-96 - [i4]Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos:
Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning. CoRR abs/1602.05916 (2016) - 2015
- [j5]Yunwen Lei, Lixin Ding, Wensheng Zhang:
Generalization Performance of Radial Basis Function Networks. IEEE Trans. Neural Networks Learn. Syst. 26(3): 551-564 (2015) - [c2]Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft:
Theory and Algorithms for the Localized Setting of Learning Kernels. FE@NIPS 2015: 173-195 - [c1]Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft:
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms. NIPS 2015: 2035-2043 - [i3]Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft:
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms. CoRR abs/1506.04359 (2015) - [i2]Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft:
Localized Multiple Kernel Learning - A Convex Approach. CoRR abs/1506.04364 (2015) - [i1]Yunwen Lei, Lixin Ding, Yingzhou Bi:
Local Rademacher Complexity Bounds based on Covering Numbers. CoRR abs/1510.01463 (2015) - 2014
- [j4]Yunwen Lei, Lixin Ding:
Refined Rademacher Chaos Complexity Bounds with Applications to the Multikernel Learning Problem. Neural Comput. 26(4): 739-760 (2014) - [j3]Yunwen Lei, Lixin Ding, Yiming Ding:
Generalization ability of fractional polynomial models. Neural Networks 49: 59-73 (2014) - 2013
- [j2]Yunwen Lei, Lixin Ding:
Approximation and estimation bounds for free knot splines. Comput. Math. Appl. 65(7): 1006-1024 (2013) - [j1]Yunwen Lei, Lixin Ding, Weili Wu:
Universal learning using free multivariate splines. Neurocomputing 119: 253-263 (2013)
Coauthor Index
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last updated on 2024-10-07 22:07 CEST by the dblp team
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