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How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets

How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets

14 November 2014
Zhiyun Lu
Avner May
Kuan Liu
A. Garakani
Dong Guo
A. Bellet
Linxi Fan
Michael Collins
Brian Kingsbury
M. Picheny
Fei Sha
    BDL
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Papers citing "How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets"

7 / 7 papers shown
Title
Going Deeper with Convolutions
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
333
43,511
0
17 Sep 2014
Fastfood: Approximate Kernel Expansions in Loglinear Time
Fastfood: Approximate Kernel Expansions in Loglinear Time
Quoc V. Le
Tamás Sarlós
Alex Smola
66
442
0
13 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
109
230
0
21 Jul 2014
Compact Random Feature Maps
Compact Random Feature Maps
Raffay Hamid
Ying Xiao
Alex Gittens
D. DeCoste
60
86
0
17 Dec 2013
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
385
7,650
0
03 Jul 2012
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OOD
SSL
184
12,384
0
24 Jun 2012
Random Feature Maps for Dot Product Kernels
Random Feature Maps for Dot Product Kernels
Purushottam Kar
H. Karnick
62
255
0
31 Jan 2012
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