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Yunwen Lei

Showing results (1-10 of 13) with videos related to

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IEEE Transactions on Pattern Analysis and Machine Intelligence|October 14, 2025
Towards Better Generalization Bounds of Stochastic Optimization for Nonconvex LearningYunwen Lei
Neural Computation|February 1, 2014
Refined rademacher chaos complexity bounds with applications to the multikernel learning problemYunwen Lei, Lixin Ding
IEEE Transactions on Pattern Analysis and Machine Intelligence|March 23, 2021
Learning Rates for Stochastic Gradient Descent With Nonconvex ObjectivesYunwen Lei, Ke Tang
Neural Computation|January 18, 2017
Analysis of Online Composite Mirror Descent AlgorithmYunwen Lei, Ding-Xuan Zhou
Neural Computation|May 15, 2023
Optimization and Learning With Randomly Compressed Gradient UpdatesZhanliang Huang, Yunwen Lei, Ata Kabán
IEEE Transactions on Pattern Analysis and Machine Intelligence|April 29, 2026
From Convergence to Generalization: Stability of Stationary-Point Learning AlgorithmsYunwen Lei, Zimeng Wang, Xiaoming Yuan
IEEE Transactions on Neural Networks and Learning Systems|February 27, 2015
Generalization performance of radial basis function networksYunwen Lei, Lixin Ding, Wensheng Zhang
Entropy (Basel, Switzerland)|August 28, 2025
PAC-Bayes Guarantees for Data-Adaptive Pairwise LearningSijia Zhou, Yunwen Lei, Ata Kabán
Neural Networks : the Official Journal of the International Neural Network Society|October 22, 2013
Generalization ability of fractional polynomial modelsYunwen Lei, Lixin Ding, Yiming Ding
IEEE Transactions on Neural Networks and Learning Systems|December 14, 2019
Stochastic Gradient Descent for Nonconvex Learning Without Bounded Gradient AssumptionsYunwen Lei, Ting Hu, Guiying Li, et al.
Pageof 2

Showing results (1-10 of 13) with videos related to

Sort By:
Pageof 2
IEEE Transactions on Pattern Analysis and Machine Intelligence|October 14, 2025
Towards Better Generalization Bounds of Stochastic Optimization for Nonconvex LearningYunwen Lei
Neural Computation|February 1, 2014
Refined rademacher chaos complexity bounds with applications to the multikernel learning problemYunwen Lei, Lixin Ding
IEEE Transactions on Pattern Analysis and Machine Intelligence|March 23, 2021
Learning Rates for Stochastic Gradient Descent With Nonconvex ObjectivesYunwen Lei, Ke Tang
Neural Computation|January 18, 2017
Analysis of Online Composite Mirror Descent AlgorithmYunwen Lei, Ding-Xuan Zhou
Neural Computation|May 15, 2023
Optimization and Learning With Randomly Compressed Gradient UpdatesZhanliang Huang, Yunwen Lei, Ata Kabán
IEEE Transactions on Pattern Analysis and Machine Intelligence|April 29, 2026
From Convergence to Generalization: Stability of Stationary-Point Learning AlgorithmsYunwen Lei, Zimeng Wang, Xiaoming Yuan
IEEE Transactions on Neural Networks and Learning Systems|February 27, 2015
Generalization performance of radial basis function networksYunwen Lei, Lixin Ding, Wensheng Zhang
Entropy (Basel, Switzerland)|August 28, 2025
PAC-Bayes Guarantees for Data-Adaptive Pairwise LearningSijia Zhou, Yunwen Lei, Ata Kabán
Neural Networks : the Official Journal of the International Neural Network Society|October 22, 2013
Generalization ability of fractional polynomial modelsYunwen Lei, Lixin Ding, Yiming Ding
IEEE Transactions on Neural Networks and Learning Systems|December 14, 2019
Stochastic Gradient Descent for Nonconvex Learning Without Bounded Gradient AssumptionsYunwen Lei, Ting Hu, Guiying Li, et al.
Pageof 2