Computing locally injective mappings with low distortion in an efficient way is a fundamental
task in computer graphics. By revisiting the well-known MIPS (Most-Isometric …

One of the key steps at each iteration of a randomized block coordinate descent method
consists in determining the update to a block of variables. Existing algorithms assume that in …

Introducing cooperative coded caching into small cell networks is a promising approach to
reducing traffic loads. By encoding content via maximum distance separable (MDS) codes …

In this paper, we consider the learning problem of multilayer perceptrons (MLPs) formulated
as the problem of minimizing a smooth error function. As well known, the learning problem of …

In this paper we propose an alternating block version of a variable metric linesearch
proximal gradient method. This algorithm addresses problems where the objective function …

In this paper we present a convergence rate analysis of inexact variants of several
randomized iterative methods for solving three closely related problems: a convex stochastic …

Continuous optimization is an important problem in many areas of AI, including vision,
robotics, probabilistic inference, and machine learning. Unfortunately, most real-world …

This paper considers the problem of minimizing a continuously differentiable function with a
Lipschitz continuous gradient subject to a single linear equality constraint and additional …

We present a novel randomized block coordinate descent method for the minimization of a
convex composite objective function. The method uses (approximate) partial second-order …

The alternating active-phase algorithm has recently been used to solve multi-material
topology optimization (TO) problems. The algorithm splits the multi-material problem into …