default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDYunwen Lei
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
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 - [i32]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) - [i31]Andreas Christmann, Yunwen Lei:
Bootstrap SGD: Algorithmic Stability and Robustness. CoRR abs/2409.01074 (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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-22 20:11 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
