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Condition Number Analysis of Logistic Regression, and its Implications
  for Standard First-Order Solution Methods

Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods

20 October 2018
R. Freund
Paul Grigas
Rahul Mazumder
ArXivPDFHTML

Papers citing "Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods"

3 / 3 papers shown
Title
The phase transition for the existence of the maximum likelihood
  estimate in high-dimensional logistic regression
The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression
Emmanuel J. Candes
Pragya Sur
34
140
0
25 Apr 2018
Convergence of Gradient Descent on Separable Data
Convergence of Gradient Descent on Separable Data
Mor Shpigel Nacson
Jason D. Lee
Suriya Gunasekar
Pedro H. P. Savarese
Nathan Srebro
Daniel Soudry
58
167
0
05 Mar 2018
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic
  Programming
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming
Saeed Ghadimi
Guanghui Lan
ODL
68
1,538
0
22 Sep 2013
1