— We propose a randomized data mining method that finds clusters of spatially overlapping images. The core of the method relies on the min-Hash algorithm for fast detection of p...
The dynamic hierarchical Dirichlet process (dHDP) is developed to model the timeevolving statistical properties of sequential data sets. The data collected at any time point are r...
In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
In this paper, a new class of audio representations is introduced, together with a corresponding fast decomposition algorithm. The main feature of these representations is that th...
Statistical estimation and approximate query processing have become increasingly prevalent applications for database systems. However, approximation is usually of little use witho...