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Sparsity-constrained optimization has wide applicability in machine learning, statistics, and signal processing problems such as feature selection and compressive Sensing.
Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition
Y. C. Pati, R. Rezaiifar, and P. S. Krishnaprasad · 1993
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Time Series Analysis
J. D. Hamilton · 1994
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Sparse approximate solutions to linear systems
B. K. Natarajan · 1995
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Statistical learning theory
V. Vapnik · 1998
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Empirical processes in M-estimation
S. A. van de Geer · 2000
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Uncertainty principles and ideal atomic decomposition
D. Donoho and X. Huo · 2001
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Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ 1 \ell_{1} minimization
D. L. Donoho and M. Elad · 2003
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Result analysis of the nips 2003 feature selection challenge, 2003
I. Guyon, S. Gunn, A. Ben Hur, and G. Dror · 2003
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Stable signal recovery from incomplete and inaccurate measurements
E. J. Candès, J. K. Romberg, and T. Tao · 2006
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Compressed sensing
D. L. Donoho · 2006
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Signal recovery from random measurements via orthogonal matching pursuit
J. A. Tropp and A. C. Gilbert · 2007
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Honest variable selection in linear and logistic regression models via ℓ 1 \ell_{1} and ℓ 1 + ℓ 2 \ell_{1}+\ell_{2} penalization
F. Bunea · 2008
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The restricted isometry property and its implications for compressed sensing
E. J. Candès · 2008
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An Introduction to Generalized Linear Models
A. J. Dobson and A. Barnett · 2008
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High-dimensional generalized linear models and the lasso
S. A. van de Geer · 2008
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Simultaneous analysis of lasso and dantzig selector
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Iterative hard thresholding for compressed sensing
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Compressed sensing with nonlinear observations
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Regularization paths for generalized linear models via coordinate descent
J. H. Friedman, T. Hastie, and R. Tibshirani · 2010
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Learning exponential families in high-dimensions: Strong convexity and sparsity
S. M. Kakade, O. Shamir, K. Sridharan, and A. Tewari · 2010
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Trading accuracy for sparsity in optimization problems with sparsity constraints
S. Shalev-Shwartz, N. Srebro, and T. Zhang · 2010
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Greedy sparsity-constrained optimization
S. Bahmani, P. Boufounos, and B. Raj · 2011
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On learning discrete graphical models using greedy methods
A. Jalali, C. C. Johnson, and P. K. Ravikumar · 2011
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The elements of statistical learning: data mining, inference, and prediction
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Large-scale sparse logistic regression
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CoSaMP: iterative signal recovery from incomplete and inaccurate samples
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A unified framework for high-dimensional analysis of m m -estimators with decomposable regularizers
S. Negahban, P. Ravikumar, M. Wainwright, and B. Yu · 2009
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Fast global convergence rates of gradient methods for high-dimensional statistical recovery
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Group orthogonal matching pursuit for logistic regression
A. Lozano, G. Swirszcz, and N. Abe · 2011
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Greedy algorithms for structurally constrained high dimensional problems
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User-friendly tail bounds for sums of random matrices
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Sparse recovery with orthogonal matching pursuit under RIP
T. Zhang · 2011
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Sparse recovery algorithms: sufficient conditions in terms of restricted isometry constants
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Efficiency of coordinate descent methods on huge-scale optimization problems
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