Singular Value Decomposition (SVD), together with the Expectation-Maximization (EM) procedure, can be used to find a low-dimension model that maximizes the loglikelihood of obser...
Sheng Zhang, Weihong Wang, James Ford, Fillia Make...
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...
Abstract. In this paper we show how using a representation of an elliptic curve as the intersection of two quadrics in P3 can provide a defence against Simple and Differental Powe...
Visual tracking is a key component in many computer vision applications. Linear subspace techniques (e.g. eigentracking) are one of the most popular approaches to align templates ...
Jose Gonzalez-Mora, Nicolas Guil, Emilio L. Zapata...
Before the advent of Hidden Markov Models(HMM)-based speech recognition, many speech applications were built using pattern matching algorithms like the Dynamic Time Warping (DTW) ...