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ICCV
2011
IEEE
13 years 9 months ago
Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
Matthew D. Zeiler, Graham W. Taylor, Rob Fergus
71
Voted
ICIC
2005
Springer
15 years 3 months ago
Improvements to the Conventional Layer-by-Layer BP Algorithm
This paper points out some drawbacks and proposes some modifications to the conventional layer-by-layer BP algorithm. In particular, we present a new perspective to the learning ra...
Xu-Qin Li, Fei Han, Tat-Ming Lok, Michael R. Lyu, ...
67
Voted
NECO
2010
129views more  NECO 2010»
14 years 8 months ago
A Two-Layer Model of Natural Stimuli Estimated with Score Matching
We consider a hierarchical two-layer model of natural signals in which both layers are learned from the data. Estimation is accomplished by Score Matching, a recently proposed est...
Urs Köster, Aapo Hyvärinen
BICA
2010
14 years 4 months ago
Application Feedback in Guiding a Deep-Layered Perception Model
Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference ...
Itamar Arel, Shay Berant
ICMCS
2009
IEEE
137views Multimedia» more  ICMCS 2009»
14 years 7 months ago
Fractional compensation for spatial scalable video coding
This paper proposes a novel fractional compensation approach for spatial scalable video coding. It simultaneously exploits inter layer correlation and intra layer correlation by l...
Xiaoyan Sun, Feng Wu