Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
This paper presents a new way of formalizing the Coalition Structure Generation problem (CSG), so that we can apply constraint optimization techniques to it. Forming effective coal...
Naoki Ohta, Vincent Conitzer, Ryo Ichimura, Yuko S...
Composition theorems in simulation-based approaches allow to build complex protocols from sub-protocols in a modular way. However, as first pointed out and studied by Canetti and ...
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Abstract. This paper describes how function-based shape modeling can be expanded to web visualization, as well as how web-based visualization can be greatly improved by using the f...