Transfer learning addresses the problem of how to leverage knowledge acquired in a source domain to improve the accuracy and speed of learning in a related target domain. This pap...
Lilyana Mihalkova, Tuyen N. Huynh, Raymond J. Moon...
Abstract. In this paper, we study an efficient approximate integer linear programming formulation of the general problem of one-dimensional periodic task scheduling under storage r...
This paper studies local-control strategies to estimate the size of a certain event affecting an arbitrary connected subset of nodes in a network. For example, our algorithms allow...
Marcin Bienkowski, Leszek Gasieniec, Marek Klonows...
This paper discusses the use of cognitive models as augmented metacognition on task allocation for tasks requiring visual attention. In the domain of naval warfare, the complex and...
Tibor Bosse, Willem A. van Doesburg, Peter-Paul va...
Continuous attractor neural networks (CANNs) are emerging as promising models for describing the encoding of continuous stimuli in neural systems. Due to the translational invaria...