To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
In this paper, we introduce an assumption which makes it possible to extend the learning ability of discriminative model to unsupervised setting. We propose an informationtheoreti...
—Clusters and applications continue to grow in size while their mean time between failure (MTBF) is getting smaller. Checkpoint/Restart is becoming increasingly important for lar...
Abstract. Nearest neighbor searching is a fundamental computational problem. A set of n data points is given in real d-dimensional space, and the problem is to preprocess these poi...
In this paper, we present a novel visual analytics system named Newdle with a focus on exploring large online news collections when the semantics of the individual news articles ha...