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JMLR
2010
125views more  JMLR 2010»
13 years 10 days ago
Regret Bounds for Gaussian Process Bandit Problems
Bandit algorithms are concerned with trading exploration with exploitation where a number of options are available but we can only learn their quality by experimenting with them. ...
Steffen Grünewälder, Jean-Yves Audibert,...
ICONIP
2009
13 years 3 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
ICASSP
2011
IEEE
12 years 9 months ago
Rao-Blackwellized particle filter for Gaussian mixture models and application to visual tracking
One of the most important problems in visual tracking is how to incrementally update the appearance model because the appearance of a target object can be easily changed with time...
Jungho Kim, In-So Kweon
ICASSP
2011
IEEE
12 years 9 months ago
Distributed Gaussian particle filtering using likelihood consensus
We propose a distributed implementation of the Gaussian particle filter (GPF) for use in a wireless sensor network. Each sensor runs a local GPF that computes a global state esti...
Ondrej Hlinka, Ondrej Sluciak, Franz Hlawatsch, Pe...
ESSMAC
2003
Springer
13 years 10 months ago
Filtered Gaussian Processes for Learning with Large Data-Sets
Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those me...
Jian Qing Shi, Roderick Murray-Smith, D. M. Titter...