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DSP
2007
15 years 4 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...
119
Voted
PAMI
2008
135views more  PAMI 2008»
15 years 4 months ago
MultiK-MHKS: A Novel Multiple Kernel Learning Algorithm
In this paper, we develop a new effective multiple kernel learning algorithm. First, we map the input data into m different feature spaces by m empirical kernels, where each genera...
Zhe Wang, Songcan Chen, Tingkai Sun
ECCV
2010
Springer
15 years 8 months ago
Automatic Learning of Background Semantics in Generic Surveilled Scenes
Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analy...
Carles Fernández, Jordi Gonzàlez, Xavier Roca
BMVC
2010
15 years 3 months ago
Label propagation in complex video sequences using semi-supervised learning
We propose a novel directed graphical model for label propagation in lengthy and complex video sequences. Given hand-labelled start and end frames of a video sequence, a variation...
Ignas Budvytis, Vijay Badrinarayanan, Roberto Cipo...
208
Voted
AROBOTS
2011
14 years 12 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox