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MANSCI
2007
100views more  MANSCI 2007»
13 years 8 months ago
Dynamic Assortment with Demand Learning for Seasonal Consumer Goods
Companies such as Zara and World Co. have recently implemented novel product development processes and supply chain architectures enabling them to make more product design and ass...
Felipe Caro, Jérémie Gallien
BMVC
2010
13 years 6 months ago
Label propagation in complex video sequences using semi-supervised learning
We propose a novel directed graphical model for label propagation in lengthy and complex video sequences. Given hand-labelled start and end frames of a video sequence, a variation...
Ignas Budvytis, Vijay Badrinarayanan, Roberto Cipo...
ICCV
2009
IEEE
13 years 5 months ago
Real-time visual tracking via Incremental Covariance Tensor Learning
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed t...
Yi Wu, Jian Cheng, Jinqiao Wang, Hanqing Lu
AROBOTS
2011
13 years 3 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox
ICASSP
2011
IEEE
12 years 11 months ago
Denoising of image patches via sparse representations with learned statistical dependencies
We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
Tomer Faktor, Yonina C. Eldar, Michael Elad