We investigate an improvement to GSAT which associates a weight with each clause. We change the objective function so that GSAT moves to assignments maximizing the weight of satis...
Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
Chen Change Loy, Timothy M. Hospedales, Tao Xiang,...
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Abstract. We give a general framework for approximate query processing in semistructured databases. We focus on regular path queries, which are the integral part of most of the que...
: We present the implementation of on-line Hebbian learning for NESPINN, the Neurocomputer for the simulation of spiking neurons. In order to support various forms of Hebbian learn...