Stochastic DCA for minimizing a large sum of DC functions with application to Multi-class Logistic Regression

no code implementations • 10 Nov 2019 • Hoai An Le Thi, Hoai Minh Le, Duy Nhat Phan, Bach Tran

We consider the large sum of DC (Difference of Convex) functions minimization problem which appear in several different areas, especially in stochastic optimization and machine learning.

Multi-Task Learning Stochastic Optimization

A DCA-Like Algorithm and its Accelerated Version with Application in Data Visualization

no code implementations • 25 Jun 2018 • Hoai An Le Thi, Hoai Minh Le, Duy Nhat Phan, Bach Tran

In the first variant, DCA-Like, we introduce a new technique to iteratively modify the decomposition of the objective function.

Data Visualization

Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification

no code implementations • ICML 2017 • Hoai An Le Thi, Hoai Minh Le, Duy Nhat Phan, Bach Tran

In this paper, we present a stochastic version of DCA (Difference of Convex functions Algorithm) to solve a class of optimization problems whose objective function is a large sum of non-convex functions and a regularization term.

General Classification Variable Selection

DC approximation approaches for sparse optimization

no code implementations • 1 Jul 2014 • Hoai An Le Thi, Tao Pham Dinh, Hoai Minh Le, Xuan Thanh Vo

Considering a common DC approximation of the zero-norm including all standard sparse inducing penalty functions, we studied the consistency between global minimums (resp.

feature selection