Fetching the paper…
Reading the bibliography…
Random projections or sketching are widely used in many algorithmic and learning contexts.
Distribution of eigenvalues for some sets of random matrices
V. A. Marchenko and L. A. Pastur · 1967
Earlier work this paper cites.
Free random variables
D. V. Voiculescu, K. J. Dykema, and A. Nica · 1992
Earlier work this paper cites.
The random projection method
S. S. Vempala · 2005
Earlier work this paper cites.
Approximate nearest neighbors and the fast johnson-lindenstrauss transform
N. Ailon and B. Chazelle · 2006
Earlier work this paper cites.
The semicircle law, free random variables and entropy
F. Hiai and D. Petz · 2006
Earlier work this paper cites.
Lectures on the combinatorics of free probability
A. Nica and R. Speicher · 2006
Earlier work this paper cites.
Improved approximation algorithms for large matrices via random projections
T. Sarlos · 2006
Earlier work this paper cites.
A fast randomized algorithm for overdetermined linear least-squares regression
V. Rokhlin and M. Tygert · 2008
Earlier work this paper cites.
An Introduction to Random Matrices
G. W. Anderson, A. Guionnet, and O. Zeitouni · 2010
Earlier work this paper cites.
Blendenpik: Supercharging lapack’s least-squares solver
H. Avron, P. Maymounkov, and S. Toledo · 2010
Earlier work this paper cites.
Spectral analysis of large dimensional random matrices
Z. Bai and J. W. Silverstein · 2010
Earlier work this paper cites.
Capacity of channels with frequency-selective and time-selective fading
A. M. Tulino, G. Caire, S. Shamai, and S. Verdú · 2010
Earlier work this paper cites.
Random Matrix Methods for Wireless Communications
R. Couillet and M. Debbah · 2011
Earlier work this paper cites.
Faster least squares approximation
P. Drineas, M. W. Mahoney, S. Muthukrishnan, and T. Sarlós · 2011
Cited alongside, same era.
Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
N. Halko, P.-G. Martinsson, and J. A. Tropp · 2011
Cited alongside, same era.
Randomized algorithms for matrices and data
M. W. Mahoney · 2011
Cited alongside, same era.
Improved analysis of the subsampled randomized hadamard transform
J. A. Tropp · 2011
Cited alongside, same era.
Topics in Random Matrix Theory
T. Tao · 2012
Cited alongside, same era.
Asymptotically liberating sequences of random unitary matrices
G. W. Anderson and B. Farrell · 2014
Cited alongside, same era.
Structural properties underlying high-quality randomized numerical linear algebra algorithms., 2016
M. W. Mahoney and P. Drineas · 2016
Later among the works it cites.
Iterative hessian sketch: Fast and accurate solution approximation for constrained least-squares
M. Pilanci and M. J. Wainwright · 2016
Later among the works it cites.
The unreasonable effectiveness of structured random orthogonal embeddings
K. M. Choromanski, M. Rowland, and A. Weller · 2017
Later among the works it cites.
Newton sketch: A near linear-time optimization algorithm with linear-quadratic convergence
M. Pilanci and M. J. Wainwright · 2017
Later among the works it cites.
Randomized sketches for kernels: Fast and optimal nonparametric regression
Y. Yang, M. Pilanci, and M. J. Wainwright · 2017
Later among the works it cites.
Asymptotics for sketching in least squares regression
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Lsrn: A parallel iterative solver for strongly over-or underdetermined systems
X. Meng, M. A. Saunders, and M. W. Mahoney · 2014
Cited alongside, same era.
Random matrix theory in statistics: A review
D. Paul and A. Aue · 2014
Cited alongside, same era.
Sketching as a tool for numerical linear algebra
D. P. Woodruff · 2014
Cited alongside, same era.
Randomized sketches of convex programs with sharp guarantees
M. Pilanci and M. J. Wainwright · 2015
Cited alongside, same era.
Randomized algorithms for low-rank matrix factorizations: sharp performance bounds
R. Witten and E. Candes · 2015
Cited alongside, same era.
Large Sample Covariance Matrices and High-Dimensional Data Analysis
J. Yao, Z. Bai, and S. Zheng · 2015
Cited alongside, same era.
E. Dobriban and S. Liu · 2019
Later among the works it cites.
Faster least squares optimization
J. Lacotte and M. Pilanci · 2019
Later among the works it cites.
High-dimensional optimization in adaptive random subspaces
J. Lacotte, M. Pilanci, and M. Pavone · 2019
Later among the works it cites.
Effective dimension adaptive sketching methods for faster regularized least-squares optimization
J. Lacotte and M. Pilanci · 2020
Closest in time.
Optimal randomized first-order methods for least-squares problems
J. Lacotte and M. Pilanci · 2020
Closest in time.
Lower bounds and a near-optimal shrinkage estimator for least squares using random projections
S. Sridhar, M. Pilanci, and A. Özgür · 2020
Closest in time.
How to reduce dimension with pca and random projections?
F. Yang, S. Liu, E. Dobriban, and D. P. Woodruff · 2020
Closest in time.