A significant input-data uncertainty is often present in practical situations. One approach to coping with this uncertainty is to describe the uncertainty with scenarios. A scenar...
Jurij Mihelic, Amine Mahjoub, Christophe Rapine, B...
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
We present a mechanism for auctioning bandwidth on a network-wide basis to end users or ISPs that will utilize it for the same time period. This mechanism consists of a set of sim...
Manos Dramitinos, George D. Stamoulis, Costas Cour...
In the ECAD area, the Test Generation (TG) problem consists in finding an input vector test for some possible diagnosis (a set of faults) of a digital circuit. Such tests may have ...
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...