Solving large, irregular graph problems efficiently is challenging. Current software systems and commodity multiprocessors do not support fine-grained, irregular parallelism wel...
Guojing Cong, Sreedhar B. Kodali, Sriram Krishnamo...
We introduce a distributed algorithm for solving large scale Support Vector Machines (SVM) problems. The algorithm divides the training set into a number of processing nodes each ...
Despite a large research effort, software distributed shared memory systems have not been widely used to run parallel applications across clusters of computers. The higher perform...
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...
We present a novel pedestrian detection system based on probabilistic component assembly. A part-based model is proposed which uses three parts consisting of head-shoulder, torso a...
Martin Rapus, Stefan Munder, Gregory Baratoff, Joa...