In supervector UBM/GMM paradigm, each acoustic file is represented by the mean parameters of a GMM model. This supervector space is used as a data representation space, which has...
Estimating divergence between two point processes, i.e. probability laws on the space of spike trains, is an essential tool in many computational neuroscience applications, such a...
We propose algorithms for tracking the boundary contour of a deforming object from an image sequence, when the nonaffine (local) deformation over consecutive frames is large and th...
Namrata Vaswani, Yogesh Rathi, Anthony J. Yezzi, A...
Space efficiency and data reliability are two primary concerns for modern storage systems. Chunk-based deduplication, which breaks up data objects into single-instance chunks that...
Space and time have not received much attention on the Semantic Web so far. While their importance has been recognized recently, existing work reduces them to simple latitude-longi...
Current exact algorithms for score-based structure discovery in Bayesian networks on n nodes run in time and space within a polynomial factor of 2n . For practical use, the space ...
We utilize effective algorithms for computing in the cohomology of a Shimura curve together with the Jacquet-Langlands correspondence to compute systems of Hecke eigenvalues assoc...
Abstract. The generative topographic mapping (GTM) has been proposed as a statistical model to represent high dimensional data by means of a sparse lattice of points in latent spac...
Coecke, Sadrzadeh, and Clark [3] developed a compositional model of meaning for distributional semantics, in which each word in a sentence has a meaning vector and the distributio...
Edward Grefenstette, Mehrnoosh Sadrzadeh, Stephen ...
In this paper, we present a system for exhibiting a Chinese landscape painting about 900 years old. There are three parts in our system: (1) we allocate a voice dubbing or backgro...
Wei Ma, Yang Liu, Yizhou Wang, Yingqing Xu, Hongbi...