28 citations · 44 across the 13 of their papers we have counts for
4 papers · 1 filter
Learning with Asymmetric Kernels: Least Squares and Feature Interpretation
Mingzhen He, Fan He, Lei Shi +2
Asymmetric kernels naturally exist in real life, e.g., for conditional probability and directed graphs. However, most of the existing kernel-based learning methods require kernels…
Generalization Properties of hyper-RKHS and its Applications
Fanghui Liu, Lei Shi, Xiaolin Huang +2
This paper generalizes regularized regression problems in a hyper-reproducing kernel Hilbert space (hyper-RKHS), illustrates its utility for kernel learning and out-of-sample exten…
Convergence of Unregularized Online Learning Algorithms
Yunwen Lei, Lei Shi, Zheng-Chu Guo
In this paper we study the convergence of online gradient descent algorithms in reproducing kernel Hilbert spaces (RKHSs) without regularization. We establish a sufficient conditio…
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network
Zhengchu Guo, Lei Shi, Qiang Wu
Distributed learning is an effective way to analyze big data. In distributed regression, a typical approach is to divide the big data into multiple blocks, apply a base regression…