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» Probability Models for High Dynamic Range Imaging
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SODA
2007
ACM
127views Algorithms» more  SODA 2007»
14 years 11 months ago
Line-of-sight networks
Random geometric graphs have been one of the fundamental models for reasoning about wireless networks: one places n points at random in a region of the plane (typically a square o...
Alan M. Frieze, Jon M. Kleinberg, R. Ravi, Warren ...
NIPS
2004
14 years 11 months ago
Probabilistic Computation in Spiking Populations
As animals interact with their environments, they must constantly update estimates about their states. Bayesian models combine prior probabilities, a dynamical model and sensory e...
Richard S. Zemel, Quentin J. M. Huys, Rama Nataraj...
ICCV
2005
IEEE
15 years 11 months ago
A Supervised Learning Framework for Generic Object Detection in Images
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
Saad Ali, Mubarak Shah
CIKM
2006
Springer
15 years 1 months ago
Resource-aware kernel density estimators over streaming data
A fundamental building block of many data mining and analysis approaches is density estimation as it provides a comprehensive statistical model of a data distribution. For that re...
Christoph Heinz, Bernhard Seeger
LREC
2008
131views Education» more  LREC 2008»
14 years 11 months ago
Learning Morphology with Morfette
Morfette is a modular, data-driven, probabilistic system which learns to perform joint morphological tagging and lemmatization from morphologically annotated corpora. The system i...
Grzegorz Chrupala, Georgiana Dinu, Josef van Genab...