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ESANN
2008
15 years 4 months ago
Learning Inverse Dynamics: a Comparison
While it is well-known that model can enhance the control performance in terms of precision or energy efficiency, the practical application has often been limited by the complexiti...
Duy Nguyen-Tuong, Jan Peters, Matthias Seeger, Ber...
RECOMB
2005
Springer
16 years 3 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
16 years 10 months ago
Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning
In this paper we present a method for learning classspecific features for recognition. Recently a greedy layerwise procedure was proposed to initialize weights of deep belief ne...
Mohammad Norouzi (Simon Fraser University), Mani R...
CVPR
2006
IEEE
16 years 5 months ago
Visible Surface Reconstruction from Normals with Discontinuity Consideration
Given a dense set of imperfect normals obtained by photometric stereo or shape from shading, this paper presents an optimization algorithm which alternately optimizes until conver...
Tai-Pang Wu, Chi-Keung Tang
ICASSP
2009
IEEE
15 years 9 months ago
RLS-weighted Lasso for adaptive estimation of sparse signals
The batch least-absolute shrinkage and selection operator (Lasso) has well-documented merits for estimating sparse signals of interest emerging in various applications, where obse...
Daniele Angelosante, Georgios B. Giannakis