— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
— In this work we show that a metaheuristic, the Variable Neighborhood Search (VNS), can be effectively used in order to improve the performance of the hardware–friendly versio...
— Distributed Denial of Service attacks pose a serious threat to many businesses which rely on constant availability of their network services. Companies like Google, Yahoo and A...
Abstract. We present a method to find the exact maximal margin hyperplane for linear Support Vector Machines when a new (existing) component is added (removed) to (from) the inner...
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...