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IROS
2008
IEEE
211views Robotics» more  IROS 2008»
15 years 8 months ago
GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Jonathan Ko, Dieter Fox
107
Voted
NIPS
2008
15 years 3 months ago
The Mondrian Process
We describe a novel class of distributions, called Mondrian processes, which can be interpreted as probability distributions over kd-tree data structures. Mondrian processes are m...
Daniel M. Roy, Yee Whye Teh
ECCV
2006
Springer
16 years 3 months ago
Video and Image Bayesian Demosaicing with a Two Color Image Prior
Abstract. The demosaicing process converts single-CCD color representations of one color channel per pixel into full per-pixel RGB. We introduce a Bayesian technique for demosaicin...
Eric P. Bennett, Matthew Uyttendaele, C. Lawrence ...
ICDM
2010
IEEE
200views Data Mining» more  ICDM 2010»
14 years 11 months ago
Bayesian Maximum Margin Clustering
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
Bo Dai, Baogang Hu, Gang Niu
NIPS
2008
15 years 3 months ago
Bayesian Kernel Shaping for Learning Control
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
Jo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakum...