Lei Shi

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 36

Top Topics

Gaussian Kernels

Online Learning

Loss Minimization

Top Venues

J. Mach. Learn. Res.

IEEE Trans. Neural Networks Learn. Syst.

Signal Process.

Publications

Zhuoqing Song, Lei Shi, Shi Pu, Ming Yan
Optimal gradient tracking for decentralized optimization. Math. Program. 207 (1) (2024)
Yuan Mao, Lei Shi, Zheng-Chu Guo
Coefficient-based regularized distribution regression. J. Approx. Theory 297 (2024)
Fan He, Mingzhen He, Lei Shi, Xiaolin Huang
Global Search and Analysis for the Nonconvex Two-Level ℓ₁ Penalty. IEEE Trans. Neural Networks Learn. Syst. 35 (3) (2024)
Guanhang Lei, Zhen Lei, Lei Shi, Chenyu Zeng
Solving Parametric PDEs with Radial Basis Functions and Deep Neural Networks. CoRR (2024)
Fan He, Mingzhen He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens
Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning. CoRR (2024)
Guanhang Lei, Zhen Lei, Lei Shi, Chenyu Zeng, Ding-Xuan Zhou
Solving PDEs on Spheres with Physics-Informed Convolutional Neural Networks. CoRR (2023)
Fan He, Mingzhen He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens
Enhancing Kernel Flexibility via Learning Asymmetric Locally-Adaptive Kernels. CoRR (2023)
Mingzhen He, Fan He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens
Learning With Asymmetric Kernels: Least Squares and Feature Interpretation. IEEE Trans. Pattern Anal. Mach. Intell. 45 (8) (2023)
Zihan Zhang, Lei Shi, Ding-Xuan Zhou
Classification with Deep Neural Networks and Logistic Loss. CoRR (2023)
Zheng-Chu Guo, Andreas Christmann, Lei Shi
Optimality of Robust Online Learning. CoRR (2023)
Fan He, Ruikai Yang, Lei Shi, Xiaolin Huang
A Decentralized Framework for Kernel PCA with Projection Consensus Constraints. CoRR (2022)
Xin Guo, Zheng-Chu Guo, Lei Shi
Capacity dependent analysis for functional online learning algorithms. CoRR (2022)
Zhuoqing Song, Weijian Li, Kexin Jin, Lei Shi, Ming Yan, Wotao Yin, Kun Yuan
Communication-Efficient Topologies for Decentralized Learning with O(1) Consensus Rate. CoRR (2022)
Mingzhen He, Fan He, Lei Shi, Xiaolin Huang, Johan A. K. Suykens
Learning with Asymmetric Kernels: Least Squares and Feature Interpretation. CoRR (2022)
Zhuoqing Song, Weijian Li, Kexin Jin, Lei Shi, Ming Yan, Wotao Yin, Kun Yuan
Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate. NeurIPS (2022)
Yuan Mao, Lei Shi, Zheng-Chu Guo
Coefficient-based Regularized Distribution Regression. CoRR (2022)
Zhuoqing Song, Lei Shi, Shi Pu, Ming Yan
Compressed Gradient Tracking for Decentralized Optimization Over General Directed Networks. IEEE Trans. Signal Process. 70 (2022)
Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
Generalization Properties of hyper-RKHS and its Applications. J. Mach. Learn. Res. 22 (2021)
Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
Analysis of regularized least-squares in reproducing kernel Kreĭn spaces. Mach. Learn. 110 (6) (2021)
Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
Analysis of Least Squares Regularized Regression in Reproducing Kernel Krein Spaces. CoRR (2020)
Fanghui Liu, Xiaolin Huang, Lei Shi, Jie Yang, Johan A. K. Suykens
A Double-Variational Bayesian Framework in Random Fourier Features for Indefinite Kernels. IEEE Trans. Neural Networks Learn. Syst. 31 (8) (2020)
Zheng-Chu Guo, Lei Shi, Shao-Bo Lin
Realizing Data Features by Deep Nets. IEEE Trans. Neural Networks Learn. Syst. 31 (10) (2020)
Ningyu Sha, Lei Shi, Ming Yan
Fast algorithms for robust principal component analysis with an upper bound on the rank. CoRR (2020)
Lei Shi, Xiaolin Huang, Yunlong Feng, Johan A. K. Suykens
Sparse Kernel Regression with Coefficient-based $\ell_q-$regularization. J. Mach. Learn. Res. 20 (2019)
Xiaolin Huang, Haiyan Yang, Yixing Huang, Lei Shi, Fan He, Andreas K. Maier, Ming Yan
Robust mixed one-bit compressive sensing. Signal Process. 162 (2019)
Zheng-Chu Guo, Lei Shi
Fast and strong convergence of online learning algorithms. Adv. Comput. Math. 45 (5) (2019)
Zheng-Chu Guo, Lei Shi, Shao-Bo Lin
Realizing data features by deep nets. CoRR (2019)
Xiaolin Huang, Lei Shi, Ming Yan, Johan A. K. Suykens
Pinball loss minimization for one-bit compressive sensing: Convex models and algorithms. Neurocomputing 314 (2018)
Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
Generalization Properties of hyper-RKHS and its Application to Out-of-Sample Extensions. CoRR (2018)
Xiaolin Huang, Yan Xia, Lei Shi, Yixing Huang, Ming Yan, Joachim Hornegger, Andreas K. Maier
Mixed one-bit compressive sensing with applications to overexposure correction for CT reconstruction. CoRR (2017)
Zheng-Chu Guo, Lei Shi, Qiang Wu
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network. J. Mach. Learn. Res. 18 (2017)
Yunwen Lei, Lei Shi, Zheng-Chu Guo
Convergence of Unregularized Online Learning Algorithms. CoRR (2017)
Zheng-Chu Guo, Lei Shi
Fast and Strong Convergence of Online Learning Algorithms. CoRR (2017)
Xiaolin Huang, Lei Shi, Johan A. K. Suykens
Solution Path for Pin-SVM Classifiers With Positive and Negative τ Values. IEEE Trans. Neural Networks Learn. Syst. 28 (7) (2017)
Zheng-Chu Guo, Lei Shi, Qiang Wu
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network. CoRR (2017)
Yunwen Lei, Lei Shi, Zheng-Chu Guo
Convergence of Unregularized Online Learning Algorithms. J. Mach. Learn. Res. 18 (2017)
Xiaolin Huang, Yipeng Liu, Lei Shi, Sabine Van Huffel, Johan A. K. Suykens
minimization for compressed sensing. Signal Process. 108 (2015)
Xiaolin Huang, Lei Shi, Ming Yan, Johan A. K. Suykens
Pinball Loss Minimization for One-bit Compressive Sensing. CoRR (2015)
Xiaolin Huang, Lei Shi, Johan A. K. Suykens
Sequential minimal optimization for SVM with pinball loss. Neurocomputing 149 (2015)
Yunlong Feng, Xiaolin Huang, Lei Shi, Yuning Yang, Johan A. K. Suykens
Learning with the maximum correntropy criterion induced losses for regression. J. Mach. Learn. Res. 16 (2015)
Xiaolin Huang, Lei Shi, Johan A. K. Suykens
Ramp loss linear programming support vector machine. J. Mach. Learn. Res. 15 (1) (2014)
Xiaolin Huang, Lei Shi, Kristiaan Pelckmans, Johan A. K. Suykens
Asymmetric v-tube support vector regression. Comput. Stat. Data Anal. 77 (2014)
Xiaolin Huang, Lei Shi, Johan A. K. Suykens
Asymmetric least squares support vector machine classifiers. Comput. Stat. Data Anal. 70 (2014)
Xiaolin Huang, Lei Shi, Johan A. K. Suykens
Support Vector Machine Classifier With Pinball Loss. IEEE Trans. Pattern Anal. Mach. Intell. 36 (5) (2014)
Lei Shi, Xiaolin Huang, Zheng Tian, Johan A. K. Suykens
Quantile regression with ℓ 1 - regularization and Gaussian kernels. Adv. Comput. Math. 40 (2) (2014)
Zheng-Chu Guo, Lei Shi
Learning with coefficient-based regularization and ℓ1 -penalty. Adv. Comput. Math. 39 (3-4) (2013)
Zheng-Chu Guo, Lei Shi
Classification with non-i.i.d. sampling. Math. Comput. Model. 54 (5-6) (2011)
Shaogao Lv, Lei Shi
Learning theory viewpoint of approximation by positive linear operators. Comput. Math. Appl. 60 (12) (2010)
Quan-Wu Xiao, Lei Shi
Gradient Learning Approach for Variable Selection in Credit Scoring. BIFE (2009)