— In this paper we develop a new dual decomposition method for optimizing a sum of convex objective functions corresponding to multiple agents but with coupled constraints. In ou...
We consider the problem of dealing with irrelevant votes when a multi-case classifier is built from an ensemble of binary classifiers. We show how run-off elections can be used to...
The convergence rate is analyzed for the sparse reconstruction by separable approximation (SpaRSA) algorithm for minimizing a sum f(x) + ψ(x), where f is smooth and ψ is convex, ...
A lot of image analysis problems lend themselves to a unified mathematical formulation as optimization problems. Tree-serial dynamic programming is a particular case of the so-cal...
Classification is one of the most fundamental problems in machine learning, which aims to separate the data from different classes as far away as possible. A common way to get a g...
Bin Zhang, Fei Wang, Ta-Hsin Li, Wen Jun Yin, Jin ...