Abstract. In applications such as video post-production users are confronted with large amounts of redundant unedited raw material, called rushes. Viewing and organizing this mater...
In this paper, a new language model, the Multi-Class Composite N-gram, is proposed to avoid a data sparseness problem for spoken language in that it is difficult to collect traini...
Abstract. Clustering algorithms based on a matrix of pairwise similarities (kernel matrix) for the data are widely known and used, a particularly popular class being spectral clust...
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
This paper is concerned with the efficient execution of multiple query workloads on a cluster of SMPs. We target applications that access and manipulate large scientific dataset...