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NIPS
2007
13 years 7 months ago
Learning Horizontal Connections in a Sparse Coding Model of Natural Images
It has been shown that adapting a dictionary of basis functions to the statistics of natural images so as to maximize sparsity in the coefficients results in a set of dictionary ...
Pierre Garrigues, Bruno Olshausen
CVPR
2010
IEEE
14 years 2 months ago
Learning Shift-Invariant Sparse Representation of Actions
A central problem in the analysis of motion capture (Mo- Cap) data is how to decompose motion sequences into primitives. Ideally, a description in terms of primitives should fac...
Yi Li
CORR
2007
Springer
111views Education» more  CORR 2007»
13 years 6 months ago
Capacity of Sparse Multipath Channels in the Ultra-Wideband Regime
—This paper studies the ergodic capacity of time- and frequency-selective multipath fading channels in the ultrawideband (UWB) regime when training signals are used for channel e...
Vasanthan Raghavan, Gautham Hariharan, Akbar M. Sa...
TMI
2008
138views more  TMI 2008»
13 years 5 months ago
Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
ICML
2009
IEEE
14 years 6 months ago
Group lasso with overlap and graph lasso
We propose a new penalty function which, when used as regularization for empirical risk minimization procedures, leads to sparse estimators. The support of the sparse vector is ty...
Laurent Jacob, Guillaume Obozinski, Jean-Philippe ...