This paper proposes a probabilistic search algorithm to boost the computational efficiency of face detection in video sequences. The algorithm sequentially predicts the probabili...
Atsushi Matsui, Simon Clippingdale, Takashi Matsum...
A model has been developed to study the global complex dynamics of a series of blackouts in power transmission systems [1, 2]. This model has included a simple level of self-organ...
Benjamin A. Carreras, Vickie E. Lynch, Ian Dobson,...
Motivated by applications like elections, web-page ranking, revenue maximization etc., we consider the question of inferring popular rankings using constrained data. More specific...
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladi...
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...