Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
Abstract--We explore the idea of applying machine learning techniques to automatically infer risk-adaptive policies to reconfigure a network security architecture when the context ...
An innovative technique based on multi-objective grammar guided genetic programming (MOG3P-MI) is proposed to detect the most relevant activities that a student needs to pass a cou...
Abstract. In recent years several strategies for inferring gene regulatory networks from observed time series data of gene expression have been suggested based on Evolutionary Algo...
Felix Streichert, Hannes Planatscher, Christian Sp...