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» Gaussian Processes in Reinforcement Learning
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ECML
2006
Springer
14 years 1 months ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi
TIT
2002
164views more  TIT 2002»
13 years 9 months ago
On the generalization of soft margin algorithms
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
John Shawe-Taylor, Nello Cristianini
IEICET
2010
80views more  IEICET 2010»
13 years 8 months ago
Theoretical Analysis of Density Ratio Estimation
Density ratio estimation has gathered a great deal of attention recently since it can be used for various data processing tasks. In this paper, we consider three methods of densit...
Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama
CVPR
2012
IEEE
12 years 2 days ago
From pixels to physics: Probabilistic color de-rendering
Consumer digital cameras use tone-mapping to produce compact, narrow-gamut images that are nonetheless visually pleasing. In doing so, they discard or distort substantial radiomet...
Ying Xiong, Kate Saenko, Trevor Darrell, Todd Zick...
NIPS
2008
13 years 11 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink