Aug 30, 2013 · Abstract: The task of sparse linear regression consists of finding an unknown sparse vector from linear measurements.
Abstract—The task of sparse linear regression consists of finding an unknown sparse vector from linear measurements.
Jun 29, 2011 · We present a new method for multiple sparse linear regression that can leverage support and parameter overlap when it exists, but not pay a ...
Abstract—Sparse linear regression – finding an unknown vector from linear measurements – is now known to be possible with fewer samples than variables, ...
Abstract—The task of sparse linear regression consists of finding an unknown sparse vector from linear measurements. Solving this.
We present a new method for multiple sparse linear regression that can leverage support and parameter overlap when it exists, but not pay a penalty when it does ...
In this paper we take a first step, focusing on such dirty models for a specific problem: simultaneously sparse multiple regression. Our approach uses a ...
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Here, we take a first step, focusing on developing a dirty model for the multiple regression problem. Our method uses a very simple idea: we decompose the ...
Imposing sparse + group-sparse superposition structures in high-dimensional parameter estima- tion is known to provide flexible regularization.
» A Dirty Model for Multiple Sparse Regression. A. Jalali, P. Ravikumar, S. Sanghavi. IEEE Transactions on Information Theory, Vol. 59, No. 12, pages 7947 ...