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Sub-sampled Newton Methods with Non-uniform Sampling

Sub-sampled Newton Methods with Non-uniform Sampling

2 July 2016
Peng Xu
Jiyan Yang
Farbod Roosta-Khorasani
Christopher Ré
Michael W. Mahoney
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Papers citing "Sub-sampled Newton Methods with Non-uniform Sampling"

13 / 13 papers shown
Title
Second-Order Stochastic Optimization for Machine Learning in Linear Time
Second-Order Stochastic Optimization for Machine Learning in Linear Time
Naman Agarwal
Brian Bullins
Elad Hazan
ODL
40
102
0
12 Feb 2016
Sub-Sampled Newton Methods II: Local Convergence Rates
Sub-Sampled Newton Methods II: Local Convergence Rates
Farbod Roosta-Khorasani
Michael W. Mahoney
58
84
0
18 Jan 2016
Sub-Sampled Newton Methods I: Globally Convergent Algorithms
Sub-Sampled Newton Methods I: Globally Convergent Algorithms
Farbod Roosta-Khorasani
Michael W. Mahoney
49
89
0
18 Jan 2016
Convergence rates of sub-sampled Newton methods
Convergence rates of sub-sampled Newton methods
Murat A. Erdogdu
Andrea Montanari
64
157
0
12 Aug 2015
Newton Sketch: A Linear-time Optimization Algorithm with
  Linear-Quadratic Convergence
Newton Sketch: A Linear-time Optimization Algorithm with Linear-Quadratic Convergence
Mert Pilanci
Martin J. Wainwright
38
272
0
09 May 2015
Implementing Randomized Matrix Algorithms in Parallel and Distributed
  Environments
Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments
Jiyan Yang
Xiangrui Meng
Michael W. Mahoney
32
60
0
10 Feb 2015
An Introduction to Matrix Concentration Inequalities
An Introduction to Matrix Concentration Inequalities
J. Tropp
77
1,139
0
07 Jan 2015
Uniform Sampling for Matrix Approximation
Uniform Sampling for Matrix Approximation
Michael B. Cohen
Y. Lee
Cameron Musco
Christopher Musco
Richard Peng
Aaron Sidford
46
219
0
21 Aug 2014
Convex Optimization: Algorithms and Complexity
Convex Optimization: Algorithms and Complexity
Sébastien Bubeck
54
111
0
20 May 2014
Randomized Approximation of the Gram Matrix: Exact Computation and
  Probabilistic Bounds
Randomized Approximation of the Gram Matrix: Exact Computation and Probabilistic Bounds
J. Holodnak
Ilse C. F. Ipsen
62
42
0
05 Oct 2013
On the Generalization Ability of Online Learning Algorithms for Pairwise
  Loss Functions
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions
Purushottam Kar
Bharath K. Sriperumbudur
Prateek Jain
H. Karnick
53
113
0
11 May 2013
Krylov Subspace Descent for Deep Learning
Krylov Subspace Descent for Deep Learning
Oriol Vinyals
Daniel Povey
ODL
60
148
0
18 Nov 2011
Fast approximation of matrix coherence and statistical leverage
Fast approximation of matrix coherence and statistical leverage
P. Drineas
M. Magdon-Ismail
Michael W. Mahoney
David P. Woodruff
132
531
0
18 Sep 2011
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