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CORR
2010
Springer
130views Education» more  CORR 2010»
13 years 8 months ago
Approximated Structured Prediction for Learning Large Scale Graphical Models
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
Tamir Hazan, Raquel Urtasun
SIAMIS
2011
13 years 2 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
ICPR
2006
IEEE
14 years 9 months ago
Weakly Supervised Learning on Pre-image Problem in Kernel Methods
This paper presents a novel alternative approach, namely weakly supervised learning (WSL), to learn the pre-image of a feature vector in the feature space induced by a kernel. It ...
Weishi Zheng, Jian-Huang Lai, Pong Chi Yuen
NABIC
2010
13 years 2 months ago
Evolutionary design of edge detector using rule-changing Cellular automata
A new design method for Cellular automata (CA) rules are described. We have already proposed a method for designing the transition rules of two-dimensional 256-state CA for graysca...
Shohei Sato, Hitoshi Kanoh
ICCV
2009
IEEE
15 years 24 days ago
A Global Perspective on MAP Inference for Low-Level Vision
In recent years the Markov Random Field (MRF) has become the de facto probabilistic model for low-level vision applications. However, in a maximum a posteriori (MAP) framework, ...
Oliver J. Woodford, Carsten Rother, Vladimir Kolmo...