We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
We present a new machine learning method that, given a set of training examples, induces a definition of the target concept in terms of a hierarchy of intermediate concepts and th...
Blaz Zupan, Marko Bohanec, Janez Demsar, Ivan Brat...
Abstract. With ever increasing amount of available data on protein-protein interaction (PPI) networks and research revealing that these networks evolve at a modular level, discover...
We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should ...
Motivated by the study of algorithmic problems in the domain of information security, in this paper, we study the complexity of a new class of computations over a collection of va...