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» A New Discriminative Kernel From Probabilistic Models
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CVPR
2012
IEEE
13 years 5 days ago
Background modeling using adaptive pixelwise kernel variances in a hybrid feature space
Recent work on background subtraction has shown developments on two major fronts. In one, there has been increasing sophistication of probabilistic models, from mixtures of Gaussi...
Manjunath Narayana, Allen R. Hanson, Erik G. Learn...
ACCV
2010
Springer
14 years 4 months ago
Continuous Surface-Point Distributions for 3D Object Pose Estimation and Recognition
We present a 3D, probabilistic object-surface model, along with mechanisms for probabilistically integrating unregistered 2.5D views into the model, and for segmenting model instan...
Renaud Detry, Justus H. Piater
ICCV
2007
IEEE
15 years 11 months ago
Active Learning with Gaussian Processes for Object Categorization
Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate of uncertainty. Gauss...
Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Tr...
ACL
2009
14 years 7 months ago
Semantic Tagging of Web Search Queries
We present a novel approach to parse web search queries for the purpose of automatic tagging of the queries. We will define a set of probabilistic context-free rules, which genera...
Mehdi Manshadi, Xiao Li
ML
2006
ACM
121views Machine Learning» more  ML 2006»
14 years 9 months ago
Model-based transductive learning of the kernel matrix
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung