Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
Support Vector Learning Machines (SVM) are nding application in pattern recognition, regression estimation, and operator inversion for ill-posed problems. Against this very genera...
This article extends results on regular implementablity in [3] and [8] to the case when the signal space is not an injective cogenerator, for instance, the space D of compactly su...
D. Napp Avelli, Shiva Shankar, Harry L. Trentelman
The problem of automatically tuning multiple parameters for pattern recognition Support Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the gener...
Olivier Chapelle, Vladimir Vapnik, Olivier Bousque...
In this paper, we present an approach to improve the software architecture evaluation process by systematically extracting and appropriately documenting architecturally significan...