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» The Gaussian Process Density Sampler
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ICIP
2005
IEEE
14 years 11 months ago
Nonparametric clustering using quantum mechanics
This paper introduces a new nonparametric estimation approach that can be used for data that is not necessarily Gaussian distributed. The proposed approach employs the Shr?odinger...
Nikolaos Nasios, Adrian G. Bors
ICML
2009
IEEE
14 years 10 months ago
Archipelago: nonparametric Bayesian semi-supervised learning
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
Ryan Prescott Adams, Zoubin Ghahramani
ICASSP
2008
IEEE
14 years 4 months ago
Belief propagation distributed estimation in sensor networks: An optimized energy accuracy tradeoff
The estimation error performance of Gaussian belief propagation based distributed estimation in a large sensor network employing random sleep strategies is explicitly evaluated fo...
John MacLaren Walsh, Phillip A. Regalia
CDC
2009
IEEE
144views Control Systems» more  CDC 2009»
13 years 11 months ago
A minimized zero mean entropy approach to networked control systems
A novel control method is proposed for networked control systems with nonlinear process, probably non-Gaussian process noise and time delays. The performance index of closed loop c...
Jianhua Zhang, Hong Wang 0001
ICASSP
2011
IEEE
13 years 1 months ago
Bayesian sensing hidden Markov models for speech recognition
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
George Saon, Jen-Tzung Chien