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1704.02958
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On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks
10 April 2017
A. Backurs
Piotr Indyk
Ludwig Schmidt
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Papers citing
"On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks"
9 / 9 papers shown
Title
Oracle Complexity of Second-Order Methods for Finite-Sum Problems
Yossi Arjevani
Ohad Shamir
84
24
0
15 Nov 2016
Dimension-Free Iteration Complexity of Finite Sum Optimization Problems
Yossi Arjevani
Ohad Shamir
43
24
0
30 Jun 2016
Tight Complexity Bounds for Optimizing Composite Objectives
Blake E. Woodworth
Nathan Srebro
129
185
0
25 May 2016
Randomized sketches for kernels: Fast and optimal non-parametric regression
Yun Yang
Mert Pilanci
Martin J. Wainwright
82
174
0
25 Jan 2015
On the Complexity of Learning with Kernels
Nicolò Cesa-Bianchi
Yishay Mansour
Ohad Shamir
79
38
0
05 Nov 2014
On the Computational Efficiency of Training Neural Networks
Roi Livni
Shai Shalev-Shwartz
Ohad Shamir
143
480
0
05 Oct 2014
A Lower Bound for the Optimization of Finite Sums
Alekh Agarwal
Léon Bottou
162
124
0
02 Oct 2014
CNN Features off-the-shelf: an Astounding Baseline for Recognition
A. Razavian
Hossein Azizpour
Josephine Sullivan
S. Carlsson
157
4,940
0
23 Mar 2014
Sharp analysis of low-rank kernel matrix approximations
Francis R. Bach
161
282
0
09 Aug 2012
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