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» Approximate Inference and Constrained Optimization
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ICCV
2009
IEEE
15 years 18 days ago
Bayesian selection of scaling laws for motion modeling in images
Based on scaling laws describing the statistical structure of turbulent motion across scales, we propose a multiscale and non-parametric regularizer for optic-flow estimation. R...
Patrick H´eas, Etienne M´emin, Dominique Heitz, ...
PCM
2004
Springer
144views Multimedia» more  PCM 2004»
14 years 29 days ago
Dynamic Programming Based Adaptation of Multimedia Contents in UMA
Content adaptation is an effective solution to support the quality of service for multimedia services over heterogeneous networks. This paper deals with the accuracy and the real-...
Truong Cong Thang, Yong Ju Jung, Yong Man Ro
CVPR
2004
IEEE
14 years 9 months ago
Graphical Models for Graph Matching
This paper explores a formulation for attributed graph matching as an inference problem over a hidden Markov Random Field. We approximate the fully connected model with simpler mo...
Dante Augusto Couto Barone, Terry Caelli, Tib&eacu...
TMC
2011
203views more  TMC 2011»
13 years 2 months ago
Throughput Optimization in Mobile Backbone Networks
—This paper describes new algorithms for throughput optimization in a mobile backbone network. This hierarchical communication framework combines mobile backbone nodes, which hav...
Emily M. Craparo, Jonathan P. How, Eytan Modiano
EMMCVPR
2005
Springer
14 years 1 months ago
Optimizing the Cauchy-Schwarz PDF Distance for Information Theoretic, Non-parametric Clustering
This paper addresses the problem of efficient information theoretic, non-parametric data clustering. We develop a procedure for adapting the cluster memberships of the data pattern...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...