Yunwen Lei

According to our database, Yunwen Lei authored at least 73 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Few-Shot Learning With Dynamic Graph Structure Preserving.

Sichao Fu, Qiong Cao, Yunwen Lei, Yujie Zhong, Yibing Zhan, Xinge You

IEEE Trans. Ind. Informatics, March, 2024

Differentially private stochastic gradient descent with low-noise.

Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou

Neurocomputing, 2024

Generalization Analysis for Deep Contrastive Representation Learning.

Nong Minh Hieu, Antoine Ledent, Yunwen Lei, Cheng Yeaw Ku

CoRR, 2024

On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning.

Bokun Wang, Yunwen Lei, Yiming Ying, Tianbao Yang

CoRR, 2024

Bootstrap SGD: Algorithmic Stability and Robustness.

Andreas Christmann, Yunwen Lei

CoRR, 2024

Self-certified Tuple-Wise Deep Learning.

Sijia Zhou, Yunwen Lei, Ata Kabán

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems.

Jintao Song, Wenqi Lu, Yunwen Lei, Yuchao Tang, Zhenkuan Pan, Jinming Duan

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Optimization and Learning With Randomly Compressed Gradient Updates.

Zhanliang Huang, Yunwen Lei, Ata Kabán

Neural Comput., July, 2023

Pairwise Learning with Adaptive Online Gradient Descent.

Tao Sun, Qingsong Wang, Yunwen Lei, Dongsheng Li, Bao Wang

Trans. Mach. Learn. Res., 2023

Stability and Generalization for Minibatch SGD and Local SGD.

Yunwen Lei, Tao Sun, Mingrui Liu

CoRR, 2023

Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks.

Puyu Wang, Yunwen Lei, Di Wang, Yiming Ying, Ding-Xuan Zhou

CoRR, 2023

Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms.

Sijia Zhou, Yunwen Lei, Ata Kabán

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Generalization Analysis for Contrastive Representation Learning.

Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou

Proceedings of the International Conference on Machine Learning, 2023

Sharper Bounds for Uniformly Stable Algorithms with Stationary Mixing Process.

Shi Fu, Yunwen Lei, Qiong Cao, Xinmei Tian, Dacheng Tao

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems.

Yunwen Lei

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings.

Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Early Stopping for Iterative Regularization with General Loss Functions.

Ting Hu, Yunwen Lei

J. Mach. Learn. Res., 2022

SGFNNs: Signed Graph Filtering-based Neural Networks for Predicting Drug-Drug Interactions.

Ming Chen, Wei Jiang, Yi Pan, Jianhua Dai, Yunwen Lei, Chunyan Ji

J. Comput. Biol., 2022

Differentially private SGDA for minimax problems.

Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Noise-Efficient Learning of Differentially Private Partitioning Machine Ensembles.

Zhanliang Huang, Yunwen Lei, Ata Kabán

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Stability and Generalization for Markov Chain Stochastic Gradient Methods.

Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks.

Mingrui Liu, Zhenxun Zhuang, Yunwen Lei, Chunyang Liao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks.

Yunwen Lei, Rong Jin, Yiming Ying

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Generalization Analysis of Adversarial Learning.

Waleed Mustafa, Yunwen Lei, Marius Kloft

Proceedings of the International Conference on Machine Learning, 2022

2021

Learning Rates for Stochastic Gradient Descent With Nonconvex Objectives.

Yunwen Lei, Ke Tang

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Stochastic Proximal AUC Maximization.

Yunwen Lei, Yiming Ying

J. Mach. Learn. Res., 2021

Generalization Performance of Multi-pass Stochastic Gradient Descent with Convex Loss Functions.

Yunwen Lei, Ting Hu, Ke Tang

J. Mach. Learn. Res., 2021

Differentially private empirical risk minimization for AUC maximization.

Puyu Wang, Zhenhuan Yang, Yunwen Lei, Yiming Ying, Hai Zhang

Neurocomputing, 2021

Differentially Private SGD with Non-Smooth Loss.

Puyu Wang, Yunwen Lei, Yiming Ying, Hai Zhang

CoRR, 2021

Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning.

Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Generalization Guarantee of SGD for Pairwise Learning.

Yunwen Lei, Mingrui Liu, Yiming Ying

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fine-grained Generalization Analysis of Inductive Matrix Completion.

Antoine Ledent, Rodrigo Alves, Yunwen Lei, Marius Kloft

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Stability and Generalization for Randomized Coordinate Descent.

Puyu Wang, Liang Wu, Yunwen Lei

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning Interpretable Concept Groups in CNNs.

Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Fine-grained Generalization Analysis of Structured Output Prediction.

Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Stability and Generalization of Stochastic Gradient Methods for Minimax Problems.

Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying

Proceedings of the 38th International Conference on Machine Learning, 2021

Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions.

Yunwen Lei, Yiming Ying

Proceedings of the 9th International Conference on Learning Representations, 2021

Stability and Differential Privacy of Stochastic Gradient Descent for Pairwise Learning with Non-Smooth Loss.

Zhenhuan Yang, Yunwen Lei, Siwei Lyu, Yiming Ying

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Fine-grained Generalization Analysis of Vector-Valued Learning.

Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks.

Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Stochastic Gradient Descent for Nonconvex Learning Without Bounded Gradient Assumptions.

Yunwen Lei, Ting Hu, Guiying Li, Ke Tang

IEEE Trans. Neural Networks Learn. Syst., 2020

Design of a novel low voltage cell lysing instrument.

Feng Jiang, Mao Li, Yunwen Lei, Jun Yu

J. Comput. Methods Sci. Eng., 2020

Sharper Generalization Bounds for Pairwise Learning.

Yunwen Lei, Antoine Ledent, Marius Kloft

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent.

Yunwen Lei, Yiming Ying

Proceedings of the 37th International Conference on Machine Learning, 2020

Stochastic Hard Thresholding Algorithms for AUC Maximization.

Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

On Performance Estimation in Automatic Algorithm Configuration.

Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Data-Dependent Generalization Bounds for Multi-Class Classification.

Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft

IEEE Trans. Inf. Theory, 2019

Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping.

Shao-Bo Lin, Yunwen Lei, Ding-Xuan Zhou

J. Mach. Learn. Res., 2019

Convergence in Probability on a Big Class of Time-Variant Evolutionary Algorithms.

Ming Chen, Yunwen Lei, Lixin Ding, Zhao Tong

Int. J. Pattern Recognit. Artif. Intell., 2019

Improved Generalisation Bounds for Deep Learning Through L^∞ Covering Numbers.

Antoine Ledent, Yunwen Lei, Marius Kloft

CoRR, 2019

A Generalization Error Bound for Multi-class Domain Generalization.

Aniket Anand Deshmukh, Yunwen Lei, Srinagesh Sharma, Ürün Dogan, James W. Cutler, Clayton Scott

CoRR, 2019

Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions.

Yunwen Lei, Ting Hu, Ke Tang

CoRR, 2019

Optimal Stochastic and Online Learning with Individual Iterates.

Yunwen Lei, Peng Yang, Ke Tang, Ding-Xuan Zhou

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Learning Theory of Randomized Sparse Kaczmarz Method.

Yunwen Lei, Ding-Xuan Zhou

SIAM J. Imaging Sci., 2018

Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning.

Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos

J. Mach. Learn. Res., 2018

Refined bounds for online pairwise learning algorithms.

Xiaming Chen, Yunwen Lei

Neurocomputing, 2018

Convergence of Online Mirror Descent Algorithms.

Yunwen Lei, Ding-Xuan Zhou

CoRR, 2018

Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities.

Yunwen Lei, Ke Tang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Generalization Bounds for Regularized Pairwise Learning.

Yunwen Lei, Shao-Bo Lin, Ke Tang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

An Enhanced Firefly Algorithm with Orthogonal Centroid Opposition-Based Learning.

Lingyun Zhou, Lixin Ding, Yunwen Lei

Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

2017

Analysis of Online Composite Mirror Descent Algorithm.

Yunwen Lei, Ding-Xuan Zhou

Neural Comput., 2017

Convergence of Unregularized Online Learning Algorithms.

Yunwen Lei, Lei Shi, Zheng-Chu Guo

J. Mach. Learn. Res., 2017

Online pairwise learning algorithms with convex loss functions.

Junhong Lin, Yunwen Lei, Bo Zhang, Ding-Xuan Zhou

Inf. Sci., 2017

Generalization Error Bounds for Extreme Multi-class Classification.

Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft

CoRR, 2017

2016

Local Rademacher complexity bounds based on covering numbers.

Yunwen Lei, Lixin Ding, Yingzhou Bi

Neurocomputing, 2016

Localized Multiple Kernel Learning - A Convex Approach.

Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft

Proceedings of The 8th Asian Conference on Machine Learning, 2016

2015

Generalization Performance of Radial Basis Function Networks.

Yunwen Lei, Lixin Ding, Wensheng Zhang

IEEE Trans. Neural Networks Learn. Syst., 2015

Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms.

Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Theory and Algorithms for the Localized Setting of Learning Kernels.

Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft

Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, 2015

2014

Generalization ability of fractional polynomial models.

Yunwen Lei, Lixin Ding, Yiming Ding

Neural Networks, 2014

Refined Rademacher Chaos Complexity Bounds with Applications to the Multikernel Learning Problem.

Yunwen Lei, Lixin Ding

Neural Comput., 2014

2013

Universal learning using free multivariate splines.

Yunwen Lei, Lixin Ding, Weili Wu

Neurocomputing, 2013

Approximation and estimation bounds for free knot splines.

Yunwen Lei, Lixin Ding

Comput. Math. Appl., 2013