Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this...
Adriano L. I. Oliveira, Fernando Buarque de Lima N...
Abstract. Protein-protein interactions play a major role in most cellular processes. Thus, the challenge of identifying the full repertoire of interacting proteins in the cell is o...
Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir F...
Many real life problems require the classification of items into naturally ordered classes. These problems are traditionally handled by conventional methods intended for the class...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...