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» Learning Object Representations Using Sequential Patterns
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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
CVPR
2011
IEEE
13 years 4 months ago
Learning to Recognize Objects in Egocentric Activities
This paper addresses the problem of learning object models from egocentric video of household activities, using extremely weak supervision. For each activity sequence, we know onl...
Alireza Fathi, Xiaofeng Ren, James Rehg
ICML
2009
IEEE
14 years 8 months ago
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
VSTTE
2010
Springer
13 years 6 months ago
Local Reasoning and Dynamic Framing for the Composite Pattern and Its Clients
Abstract. The Composite design pattern is an exemplar of specification and verification challenges for sequential object-oriented programs. Region logic is a Hoare logic augmente...
Stan Rosenberg, Anindya Banerjee, David A. Naumann
TRS
2008
13 years 7 months ago
Generalized Indiscernibility Relations: Applications for Missing Values and Analysis of Structural Objects
In this paper, we discuss an approach to structural objects based on a generalisation of indiscernibility relation used in rough set theory. The existing results in rough set theor...
Wojciech Jaworski