In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimiza...
We study the classic mathematical economics problem of Bayesian optimal mechanism design where a principal aims to optimize expected revenue when allocating resources to self-inte...
Shuchi Chawla, Jason Hartline, David Malec and Bal...
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
In this paper we describe a multi-objective problem solving approach, simultaneously minimizing average surface roughness Ra and build Time T, for object manufacturing by Rapid Pr...
This paper proposes a clustering method SOMAK, which is composed by Self-Organizing Maps (SOM) followed by the Ant K-means (AK) algorithm. The aim of this method is not to find an...
Jefferson R. Souza, Teresa Bernarda Ludermir, Lean...