We show that several important Bayesian bounds studied in machine learning, both in the batch as well as the online setting, arise by an application of a simple compression lemma....
Model compensation schemes are a powerful approach to handling mismatches between training and testing conditions. Normally these schemes are run in a batch adaptation mode, re-re...
Abstract. Protein membership prediction is a fundamental task to retrieve information for unknown or unidentified sequences. When support vector machines (SVMs) are associated with...
This paper is concerned with the efficient execution of multiple query workloads on a cluster of SMPs. We target applications that access and manipulate large scientific dataset...
Abstract. In this paper we propose a new method to perform incremental discretization. The basic idea is to perform the task in two layers. The first layer receives the sequence o...