We propose in this paper a novel approach to the induction of the structure of Hidden Markov Models. The induced model is seen as a lumped process of a Markov chain. It is construc...
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
We consider parameterized convex optimization problems over the unit simplex, that depend on one parameter. We provide a simple and efficient scheme for maintaining an -approximat...
Evolutionary support vector machines (ESVMs) are a novel technique that assimilates the learning engine of the state-of-the-art support vector machines (SVMs) but evolves the coef...
Ruxandra Stoean, Dumitru Dumitrescu, Mike Preuss, ...
This paper presents a new information acquisition problem motivated by business applications where customer data has to be acquired with a specific modeling objective in mind. In ...