Proximal gradient methods for learning

Known as: Proximal gradient

Proximal gradient (forward backward splitting) methods for learning is an area of research in optimization and statistical learning theory which…

Papers overview

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2017

In this letter, we present a novel visual tracking algorithm based on sparse representation. In contrast to just use the target…

2017

We consider a primal-dual algorithm for minimizing $f(x)+h(Ax)$ with differentiable $f$. The primal-dual algorithm has two names…

Review

2017

Review

2017

This work addresses image recovery problem in the presence of salt-and-pepper noise and image blur. The salt-and-pepper noise…

2016

In the era of the Internet of Things, enormous number of sensors have been deployed in different locations, generating massive…

2016

In this paper, we propose a stochastic proximal gradient method to train ternary weight neural networks (TNN). The proposed…

2015

The connection between online users is the key to the success of many important applications, such as viral marketing. In reality…

2014

2014

2013

In this paper we propose a randomized block coordinate non-monotone gradient (RBCNMG) method for minimizing the sum of a smooth…

2006

Many techniques have been developed to enhance innovative thinking within a company. However, many innovations never make it…