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» Learning Gaussian Process Models from Uncertain Data
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GI
2007
Springer
14 years 2 months ago
Background Modeling Using Adaptive Cluster Density Estimation for Automatic Human Detection
: Detection is an inherent part of every advanced automatic tracking system. In this work we focus on automatic detection of humans by enhanced background subtraction. Background s...
Harish Bhaskar, Lyudmila Mihaylova, Simon Maskell
ICMLA
2008
13 years 10 months ago
Semi-supervised IFA with Prior Knowledge on the Mixing Process: An Application to a Railway Device Diagnosis
Independent Factor Analysis (IFA) is a well known method used to recover independent components from their linear observed mixtures without any knowledge on the mixing process. Su...
Etienne Côme, Zohra Leila Cherfi, Latifa Ouk...
CORR
2010
Springer
134views Education» more  CORR 2010»
13 years 7 months ago
The LASSO risk for gaussian matrices
We consider the problem of learning a coefficient vector x0 ∈ RN from noisy linear observation y = Ax0 + w ∈ Rn . In many contexts (ranging from model selection to image proce...
Mohsen Bayati, Andrea Montanari
JCDL
2006
ACM
161views Education» more  JCDL 2006»
14 years 2 months ago
Learning metadata from the evidence in an on-line citation matching scheme
Citation matching, or the automatic grouping of bibliographic references that refer to the same document, is a data management problem faced by automatic digital libraries for sci...
Isaac G. Councill, Huajing Li, Ziming Zhuang, Sand...
ICML
2007
IEEE
14 years 9 months ago
Bayesian actor-critic algorithms
We1 present a new actor-critic learning model in which a Bayesian class of non-parametric critics, using Gaussian process temporal difference learning is used. Such critics model ...
Mohammad Ghavamzadeh, Yaakov Engel