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On Data Preconditioning for Regularized Loss Minimization

On Data Preconditioning for Regularized Loss Minimization

13 August 2014
Tianbao Yang
Rong Jin
Shenghuo Zhu
Qihang Lin
ArXivPDFHTML

Papers citing "On Data Preconditioning for Regularized Loss Minimization"

6 / 6 papers shown
Title
Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters
Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters
Zeyuan Allen-Zhu
Yang Yuan
Karthik Sridharan
20
27
0
05 Feb 2016
Matrix Coherence and the Nystrom Method
Matrix Coherence and the Nystrom Method
Ameet Talwalkar
Afshin Rostamizadeh
96
88
0
09 Aug 2014
Scalable Kernel Methods via Doubly Stochastic Gradients
Scalable Kernel Methods via Doubly Stochastic Gradients
Bo Dai
Bo Xie
Niao He
Yingyu Liang
Anant Raj
Maria-Florina Balcan
Le Song
46
227
0
21 Jul 2014
A Proximal Stochastic Gradient Method with Progressive Variance
  Reduction
A Proximal Stochastic Gradient Method with Progressive Variance Reduction
Lin Xiao
Tong Zhang
ODL
93
737
0
19 Mar 2014
Stochastic Gradient Descent for Non-smooth Optimization: Convergence
  Results and Optimal Averaging Schemes
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes
Ohad Shamir
Tong Zhang
104
572
0
08 Dec 2012
Sharp analysis of low-rank kernel matrix approximations
Sharp analysis of low-rank kernel matrix approximations
Francis R. Bach
88
281
0
09 Aug 2012
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