33 citations · 64 across the 10 of their papers we have counts for
6 papers · 1 filter
Nonconvex Penalization in Sparse Estimation: An Approach Based on the Bernstein Function
Zhihua Zhang
In this paper we study nonconvex penalization using Bernstein functions whose first-order derivatives are completely monotone. The Bernstein function can induce a class of nonconve…
The Bernstein Function: A Unifying Framework of Nonconvex Penalization in Sparse Estimation
Zhihua Zhang
In this paper we study nonconvex penalization using Bernstein functions. Since the Bernstein function is concave and nonsmooth at the origin, it can induce a class of nonconvex fun…
The Matrix Ridge Approximation: Algorithms and Applications
Zhihua Zhang
We are concerned with an approximation problem for a symmetric positive semidefinite matrix due to motivation from a class of nonlinear machine learning methods. We discuss an appr…
Kinetic Energy Plus Penalty Functions for Sparse Estimation
Zhihua Zhang, Shibo Zhao, Zebang Shen +1
In this paper we propose and study a family of sparsity-inducing penalty functions. Since the penalty functions are related to the kinetic energy in special relativity, we call the…
EP-GIG Priors and Applications in Bayesian Sparse Learning
Zhihua Zhang, Shusen Wang, Dehua Liu +1
In this paper we propose a novel framework for the construction of sparsity-inducing priors. In particular, we define such priors as a mixture of exponential power distributions wi…
Coherence Functions with Applications in Large-Margin Classification Methods
Zhihua Zhang, Guang Dai, Michael I. Jordan
Support vector machines (SVMs) naturally embody sparseness due to their use of hinge loss functions. However, SVMs can not directly estimate conditional class probabilities. In thi…