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» Learning Generic Prior Models for Visual Computation
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RECOMB
2012
Springer
13 years 5 days ago
Reconstructing Boolean Models of Signaling
Abstract. Since the first emergence of protein-protein interaction networks, more than a decade ago, they have been viewed as static scaffolds of the signaling-regulatory events ...
Roded Sharan, Richard M. Karp
CAINE
2007
14 years 11 months ago
Interactive Thin Shells - A Model Interface for the Analysis of Physically-based Animation
Realism has always been a goal in computer graphics. However, the algorithms involved in mimicking ical world are often complex, abstract, and sensitive to changes in experimental...
James Skorupski, Zoë J. Wood, Alex Pang
CVPR
2008
IEEE
15 years 4 months ago
Scene understanding with discriminative structured prediction
Spatial priors play crucial roles in many high-level vision tasks, e.g. scene understanding. Usually, learning spatial priors relies on training a structured output model. In this...
Jinhui Yuan, Jianmin Li, Bo Zhang
ICML
2007
IEEE
15 years 10 months ago
Bayesian actor-critic algorithms
We1 present a new actor-critic learning model in which a Bayesian class of non-parametric critics, using Gaussian process temporal difference learning is used. Such critics model ...
Mohammad Ghavamzadeh, Yaakov Engel
CVPR
2012
IEEE
13 years 6 days ago
Weakly supervised structured output learning for semantic segmentation
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....