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ICML
2010
IEEE
14 years 10 months ago
Learning Fast Approximations of Sparse Coding
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
Karol Gregor, Yann LeCun
CVPR
2008
IEEE
15 years 11 months ago
Sparse probabilistic regression for activity-independent human pose inference
Discriminative approaches to human pose inference involve mapping visual observations to articulated body configurations. Current probabilistic approaches to learn this mapping ha...
Raquel Urtasun, Trevor Darrell
TIP
2011
170views more  TIP 2011»
14 years 4 months ago
Image Denoising in Mixed Poisson-Gaussian Noise
—We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson–Gau...
Florian Luisier, Thierry Blu, Michael Unser
SIAMJO
2008
93views more  SIAMJO 2008»
14 years 9 months ago
Smooth Optimization with Approximate Gradient
We show that the optimal complexity of Nesterov's smooth first-order optimization algorithm is preserved when the gradient is only computed up to a small, uniformly bounded er...
Alexandre d'Aspremont
ICASSP
2010
IEEE
14 years 10 months ago
Fundamental limits of image denoising: Are we there yet?
In this paper, we study the fundamental performance limits of image denoising where the aim is to recover the original image from its noisy observation. Our study is based on a ge...
Priyam Chatterjee, Peyman Milanfar