99 search results - page 19 / 20 » Learning Hidden Markov Models with Distributed State Represe... |
SAT
2010
Springer
13 years 4 months ago
2010
Springer
This paper presents a detailed empirical study of local search for Boolean satisfiability (SAT), highlighting several interesting properties, some of which were previously unknown...
ICCV
2007
IEEE
14 years 8 months ago
2007
IEEE
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
NIPS
2004
13 years 7 months ago
2004
Multiple realizations of continuous-valued time series from a stochastic process often contain systematic variations in rate and amplitude. To leverage the information contained i...
KDD
2009
ACM
14 years 6 months ago
2009
ACM
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
CVPR
2008
IEEE
14 years 8 months ago
2008
IEEE
Recently, a novel Log-Euclidean Riemannian metric [28] is proposed for statistics on symmetric positive definite (SPD) matrices. Under this metric, distances and Riemannian means ...