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CORR
2010
Springer
80views Education» more  CORR 2010»
14 years 10 months ago
Multi-path Probabilistic Available Bandwidth Estimation through Bayesian Active Learning
Knowing the largest rate at which data can be sent on an end-to-end path such that the egress rate is equal to the ingress rate with high probability can be very practical when ch...
Frederic Thouin, Mark Coates, Michael Rabbat
FASE
2011
Springer
14 years 1 months ago
Automated Learning of Probabilistic Assumptions for Compositional Reasoning
Probabilistic verification techniques have been applied to the formal modelling and analysis of a wide range of systems, from communication protocols such as Bluetooth, to nanosca...
Lu Feng, Marta Z. Kwiatkowska, David Parker
ICCV
2005
IEEE
15 years 3 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
NIPS
2003
14 years 11 months ago
A Model for Learning the Semantics of Pictures
We propose an approach to learning the semantics of images which allows us to automatically annotate an image with keywords and to retrieve images based on text queries. We do thi...
Victor Lavrenko, R. Manmatha, Jiwoon Jeon
SDM
2007
SIAM
162views Data Mining» more  SDM 2007»
14 years 11 months ago
Probabilistic Joint Feature Selection for Multi-task Learning
We study the joint feature selection problem when learning multiple related classification or regression tasks. By imposing an automatic relevance determination prior on the hypo...
Tao Xiong, Jinbo Bi, R. Bharat Rao, Vladimir Cherk...