This paper presents a novel online relevant set algorithm for a linearly-scored block sequence translation model. The key component is a new procedure to directly optimize the glob...
In this paper, we propose an online hardware task scheduling and placement algorithm and evaluate it performance. Experimental results on large random task set show that our algori...
Thomas Marconi, Yi Lu 0004, Koen Bertels, Georgi G...
Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing ...
Architectures with software-writable parameters, or configurable architectures, enable runtime reconfiguration of computing platforms to the applications they execute. Such dynami...
In this paper we present a simple to implement truly online large margin version of the Perceptron ranking (PRank) algorithm, called the OAP-BPM (Online Aggregate Prank-Bayes Poin...