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ICML
2007
IEEE
15 years 10 months ago
Most likely heteroscedastic Gaussian process regression
This paper presents a novel Gaussian process (GP) approach to regression with inputdependent noise rates. We follow Goldberg et al.'s approach and model the noise variance us...
Kristian Kersting, Christian Plagemann, Patrick Pf...
TSMC
2002
119views more  TSMC 2002»
14 years 9 months ago
Scene analysis by integrating primitive segmentation and associative memory
Scene analysis is a major aspect of perception and continues to challenge machine perception. This paper addresses the scene-analysis problem by integrating a primitive segmentatio...
DeLiang L. Wang, Xiuwen Liu
ICML
2009
IEEE
15 years 10 months ago
Partial order embedding with multiple kernels
We consider the problem of embedding arbitrary objects (e.g., images, audio, documents) into Euclidean space subject to a partial order over pairwise distances. Partial order cons...
Brian McFee, Gert R. G. Lanckriet
ICML
2000
IEEE
15 years 10 months ago
Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots
Decision-theoretic reasoning and planning algorithms are increasingly being used for mobile robot navigation, due to the signi cant uncertainty accompanying the robots' perce...
Daniel Nikovski, Illah R. Nourbakhsh
MLDM
2009
Springer
15 years 4 months ago
An Evidence-Driven Probabilistic Inference Framework for Semantic Image Understanding
This work presents an image analysis framework driven by emerging evidence and constrained by the semantics expressed in an ontology. Human perception, apart from visual stimulus a...
Spiros Nikolopoulos, Georgios Th. Papadopoulos, Io...