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Sparse principal component analysis (PCA) is a popular dimensionality reduction technique for obtaining principal components which are linear combinations of a small subset of the original features.
Analysis of a complex of statistical variables into principal components
H. Hotelling · 1933
Earlier work this paper cites.
Limits for the characteristic roots of a matrix iv
A. Brauer · 1952
Earlier work this paper cites.
The varimax criterion for analytic rotation in factor analysis
H. F. Kaiser · 1958
Earlier work this paper cites.
Two case studies in the application of principal component analysis
J. N. Jeffers · 1967
Earlier work this paper cites.
An outer-approximation algorithm for a class of mixed-integer nonlinear programs
M. A. Duran and I. E. Grossmann · 1986
Earlier work this paper cites.
Rotation of principal components
M. B. Richman · 1986
Earlier work this paper cites.
Randomized rounding: a technique for provably good algorithms and algorithmic proofs
P. Raghavan and C. D. Tompson · 1987
Earlier work this paper cites.
Matrix analysis
R. A. Horn and C. R. Johnson · 1990
Earlier work this paper cites.
An LP/NLP based branch and bound algorithm for convex MINLP optimization problems
I. Quesada and I. E. Grossmann · 1992
Earlier work this paper cites.
Linear matrix inequalities in system and control theory , volume 15
S. Boyd, L. El Ghaoui, E. Feron, and V. Balakrishnan · 1994
Earlier work this paper cites.
Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
M. X. Goemans and D. P. Williamson · 1995
Earlier work this paper cites.
Rotation of principal components: choice of normalization constraints
I. T. Jolliffe · 1995
Earlier work this paper cites.
Doubly diagonally dominant matrices
B. Li and M. Tsatsomeros · 1997
Earlier work this paper cites.
Branch-and-price: Column generation for solving huge integer programs
C. Barnhart, E. L. Johnson, G. L. Nemhauser, M. W. Savelsbergh, and P. H. Vance · 1998
Earlier work this paper cites.
Semidefinite relaxations, multivariate normal distributions, and order statistics
D. Bertsimas and Y. Ye · 1998
Earlier work this paper cites.
Second order cone programming relaxation of nonconvex quadratic optimization problems
S. Kim and M. Kojima · 2001
Earlier work this paper cites.
On tractable approximations of uncertain linear matrix inequalities affected by interval uncertainty
A. Ben-Tal and A. Nemirovski · 2002
Earlier work this paper cites.
Relaxations and randomized methods for nonconvex QCQPs
A. d’Aspremont and S. Boyd · 2003
Earlier work this paper cites.
A modified principal component technique based on the lasso
I. T. Jolliffe, N. T. Trendafilov, and M. Uddin · 2003
Earlier work this paper cites.
Convex optimization
S. Boyd and L. Vandenberghe · 2004
Earlier work this paper cites.
A well-conditioned estimator for large-dimensional covariance matrices
O. Ledoit and M. Wolf · 2004
Earlier work this paper cites.
On factor width and symmetric h-matrices
E. G. Boman, D. Chen, O. Parekh, and S. Toledo · 2005
Earlier work this paper cites.
A direct formulation for sparse pca using semidefinite programming
A. d’Aspremont, L. E. Ghaoui, M. I. Jordan, and G. R. Lanckriet · 2005
Earlier work this paper cites.
Spectral bounds for sparse pca: Exact and greedy algorithms
B. Moghaddam, Y. Weiss, and S. Avidan · 2006
Earlier work this paper cites.
Sparse principal component analysis
H. Zou, T. Hastie, and R. Tibshirani · 2006
Earlier work this paper cites.
The Dantzig selector: Statistical estimation when p is much larger than n
E. Candes and T. Tao · 2007
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Nonnegative sparse PCA
R. Zass and A. Shashua · 2007
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High-dimensional analysis of semidefinite relaxations for sparse principal components
A. A. Amini and M. J. Wainwright · 2008
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Optimal solutions for sparse principal component analysis
A. d’Aspremont, F. Bach, and L. E. Ghaoui · 2008
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The difference between 5
S. Burer, K. M. Anstreicher, and M. Dür · 2009
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A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
D. M. Witten, R. Tibshirani, and T. Hastie · 2009
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On the approximability of sparse PCA
S. O. Chan, D. Papailliopoulos, and A. Rubinstein · 2016
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Computing restricted isometry constants via mixed-integer semidefinite programming
T. Gally and M. E. Pfetsh · 2016
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Statistical and computational trade-offs in estimation of sparse principal components
T. Wang, Q. Berthet, and R. J. Samworth · 2016
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Sparse classification and phase transitions: A discrete optimization perspective
D. Bertsimas, J. Pauphilet, and B. Van Parys · 2017
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Sparse principal component analysis and its
S. S. Dey, R. Mazumder, M. Molinaro, and G. Wang · 2017
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An inverse power method for nonlinear eigenproblems with applications in 1-spectral clustering and sparse PCA
M. Hein and T. Bühler · 2010
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Generalized power method for sparse principal component analysis
M. Journée, Y. Nesterov, P. Richtárik, and R. Sepulchre · 2010
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Clustering and feature selection using sparse principal component analysis
R. Luss and A. d’Aspremont · 2010
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Graph expansion and the unique games conjecture
P. Raghavendra and D. Steurer · 2010
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Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization
B. Recht, M. Fazel, and P. A. Parrilo · 2010
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Semidefinite relaxations for quadratically constrained quadratic programming: A review and comparisons
X. Bao, N. V. Sahinidis, and M. Tawarmalani · 2011
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A randomized rounding algorithm for sparse PCA
K. Fountoulakis, A. Kundu, E.-M. Kontopoulou, and P. Drineas · 2017
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NP-hardness and inapproximability of sparse PCA
M. Magdon-Ismail · 2017
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A convex integer programming approach for optimal sparse PCA
S. S. Dey, R. Mazumder, and G. Wang · 2018
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A framework for solving mixed-integer semidefinite programs
T. Gally, M. E. Pfetsch, and S. Ulbrich · 2018
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Phase transitions in spiked matrix estimation: information-theoretic analysis
L. Miolane · 2018
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On max-k-sums
M. J. Todd · 2018
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DSOS and SDSOS optimization: More tractable alternatives to sum of squares and semidefinite optimization
A. A. Ahmadi and A. Majumdar · 2019
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Certifiably optimal sparse principal component analysis
L. Berk and D. Bertsimas · 2019
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A unified approach to mixed-integer optimization problems with logical constraints
D. Bertsimas, R. Cory-Wright, and J. Pauphilet · 2019
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Approximation hardness for a class of sparse optimization problems
Y. Chen, Y. Ye, and M. Wang · 2019
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A. Majumdar, G. Hall, and A. A. Ahmadi · 2019
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Safe screening rules for l0-regression
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On polyhedral and second-order-cone decompositions of semidefinite optimization problems
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Sparse high-dimensional regression: Exact scalable algorithms and phase transitions
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Inner approximating the completely positive cone via the cone of scaled diagonally dominant matrices
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Approximation algorithms for sparse principal component analysis
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A branch-and-cut algorithm for solving mixed-integer semidefinite optimization problems
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Exact and approximation algorithms for sparse PCA
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Alternating maximization: Unifying framework for 8 sparse PCA formulations and efficient parallel codes
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