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Variance Reduced Stochastic Proximal Algorithm for AUC Maximization
v1v2 (latest)

Variance Reduced Stochastic Proximal Algorithm for AUC Maximization

8 November 2019
Soham Dan
Dushyant Sahoo
ArXiv (abs)PDFHTML

Papers citing "Variance Reduced Stochastic Proximal Algorithm for AUC Maximization"

14 / 14 papers shown
Title
Stochastic Optimization for DC Functions and Non-smooth Non-convex
  Regularizers with Non-asymptotic Convergence
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence
Yi Tian Xu
Qi Qi
Qihang Lin
Rong Jin
Tianbao Yang
63
42
0
28 Nov 2018
Stochastic Variance Reduction Methods for Saddle-Point Problems
Stochastic Variance Reduction Methods for Saddle-Point Problems
B. Palaniappan
Francis R. Bach
119
214
0
20 May 2016
Support Vector Algorithms for Optimizing the Partial Area Under the ROC
  Curve
Support Vector Algorithms for Optimizing the Partial Area Under the ROC Curve
Harikrishna Narasimhan
S. Agarwal
32
39
0
13 May 2016
Simultaneous Model Selection and Optimization through Parameter-free
  Stochastic Learning
Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning
Francesco Orabona
140
103
0
15 Jun 2014
A Proximal Stochastic Gradient Method with Progressive Variance
  Reduction
A Proximal Stochastic Gradient Method with Progressive Variance Reduction
Lin Xiao
Tong Zhang
ODL
156
739
0
19 Mar 2014
Stochastic Optimization for Machine Learning
Stochastic Optimization for Machine Learning
Andrew Cotter
65
27
0
15 Aug 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
71
113
0
11 May 2013
One-Pass AUC Optimization
One-Pass AUC Optimization
Wei Gao
Rong Jin
Shenghuo Zhu
Zhi Zhou
98
185
0
07 May 2013
A simpler approach to obtaining an O(1/t) convergence rate for the
  projected stochastic subgradient method
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method
Simon Lacoste-Julien
Mark Schmidt
Francis R. Bach
180
260
0
10 Dec 2012
Stochastic Dual Coordinate Ascent Methods for Regularized Loss
  Minimization
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization
Shai Shalev-Shwartz
Tong Zhang
184
1,033
0
10 Sep 2012
On the Consistency of AUC Pairwise Optimization
On the Consistency of AUC Pairwise Optimization
Wei Gao
Zhi Zhou
117
124
0
03 Aug 2012
Projection-free Online Learning
Projection-free Online Learning
Elad Hazan
Satyen Kale
105
248
0
18 Jun 2012
Smoothing Multivariate Performance Measures
Smoothing Multivariate Performance Measures
Xinhua Zhang
Ankan Saha
S.V.N. Vishwanathan
72
44
0
14 Feb 2012
Making Gradient Descent Optimal for Strongly Convex Stochastic
  Optimization
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization
Alexander Rakhlin
Ohad Shamir
Karthik Sridharan
167
768
0
26 Sep 2011
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