We consider learning in situations where the function used to classify examples may switch back and forth between a small number of different concepts during the course of learnin...
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
The Support Vector Machine (SVM) methodology is an effective, supervised, machine learning method that gives stateof-the-art performance for brain state classification from funct...
Yongxin Taylor Xi, Hao Xu, Ray Lee, Peter J. Ramad...
Abstract— A distributed online learning framework for support vector machines (SVMs) is presented and analyzed. First, the generic binary classification problem is decomposed in...
Selecting which algorithms should be used by a mobile robot computer vision system is a decision that is usually made a priori by the system developer, based on past experience and...
Reinaldo A. C. Bianchi, Arnau Ramisa, Ramon L&oacu...