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Kernel Approximation Methods for Speech Recognition

Kernel Approximation Methods for Speech Recognition

13 January 2017
Avner May
A. Garakani
Zhiyun Lu
Dong Guo
Kuan Liu
A. Bellet
Linxi Fan
Michael Collins
Daniel J. Hsu
Brian Kingsbury
M. Picheny
Fei Sha
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Papers citing "Kernel Approximation Methods for Speech Recognition"

31 / 31 papers shown
Title
State-of-the-art Speech Recognition With Sequence-to-Sequence Models
State-of-the-art Speech Recognition With Sequence-to-Sequence Models
Chung-Cheng Chiu
Tara N. Sainath
Yonghui Wu
Rohit Prabhavalkar
Patrick Nguyen
...
Katya Gonina
Navdeep Jaitly
Yue Liu
J. Chorowski
M. Bacchiani
AI4TS
86
1,153
0
05 Dec 2017
A Closer Look at Memorization in Deep Networks
A Closer Look at Memorization in Deep Networks
Devansh Arpit
Stanislaw Jastrzebski
Nicolas Ballas
David M. Krueger
Emmanuel Bengio
...
Tegan Maharaj
Asja Fischer
Aaron Courville
Yoshua Bengio
Simon Lacoste-Julien
TDI
120
1,816
0
16 Jun 2017
English Conversational Telephone Speech Recognition by Humans and
  Machines
English Conversational Telephone Speech Recognition by Humans and Machines
G. Saon
Gakuto Kurata
Tom Sercu
Kartik Audhkhasi
Samuel Thomas
...
Bhuvana Ramabhadran
M. Picheny
L. Lim
Bergul Roomi
Phil Hall
65
365
0
06 Mar 2017
Understanding deep learning requires rethinking generalization
Understanding deep learning requires rethinking generalization
Chiyuan Zhang
Samy Bengio
Moritz Hardt
Benjamin Recht
Oriol Vinyals
HAI
336
4,625
0
10 Nov 2016
Diverse Neural Network Learns True Target Functions
Diverse Neural Network Learns True Target Functions
Bo Xie
Yingyu Liang
Le Song
167
137
0
09 Nov 2016
Achieving Human Parity in Conversational Speech Recognition
Achieving Human Parity in Conversational Speech Recognition
Wayne Xiong
J. Droppo
Xuedong Huang
Frank Seide
M. Seltzer
A. Stolcke
Dong Yu
Geoffrey Zweig
86
580
0
17 Oct 2016
Training variance and performance evaluation of neural networks in
  speech
Training variance and performance evaluation of neural networks in speech
E. Berg
Bhuvana Ramabhadran
M. Picheny
DRL
UQCV
29
14
0
14 Jun 2016
The IBM 2016 English Conversational Telephone Speech Recognition System
The IBM 2016 English Conversational Telephone Speech Recognition System
G. Saon
Tom Sercu
Steven J. Rennie
H. Kuo
39
0
0
27 Apr 2016
Advances in Very Deep Convolutional Neural Networks for LVCSR
Advances in Very Deep Convolutional Neural Networks for LVCSR
Tom Sercu
Vaibhava Goel
51
44
0
06 Apr 2016
Globally Normalized Transition-Based Neural Networks
Globally Normalized Transition-Based Neural Networks
D. Andor
Chris Alberti
David J. Weiss
Aliaksei Severyn
Alessandro Presta
Kuzman Ganchev
Slav Petrov
Michael Collins
82
568
0
19 Mar 2016
A Comparison between Deep Neural Nets and Kernel Acoustic Models for
  Speech Recognition
A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition
Zhiyun Lu
Dong Guo
A. Garakani
Kuan Liu
Avner May
...
Linxi Fan
Michael Collins
Brian Kingsbury
M. Picheny
Fei Sha
18
10
0
18 Mar 2016
Efficient approaches for escaping higher order saddle points in
  non-convex optimization
Efficient approaches for escaping higher order saddle points in non-convex optimization
Anima Anandkumar
Rong Ge
28
143
0
18 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
193,814
0
10 Dec 2015
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
Dario Amodei
Rishita Anubhai
Eric Battenberg
Carl Case
Jared Casper
...
Chong-Jun Wang
Bo Xiao
Dani Yogatama
J. Zhan
Zhenyao Zhu
118
2,972
0
08 Dec 2015
Listen, Attend and Spell
Listen, Attend and Spell
William Chan
Navdeep Jaitly
Quoc V. Le
Oriol Vinyals
RALM
153
2,266
0
05 Aug 2015
Learning both Weights and Connections for Efficient Neural Networks
Learning both Weights and Connections for Efficient Neural Networks
Song Han
Jeff Pool
J. Tran
W. Dally
CVBM
310
6,669
0
08 Jun 2015
Compact Nonlinear Maps and Circulant Extensions
Compact Nonlinear Maps and Circulant Extensions
Felix X. Yu
Sanjiv Kumar
H. Rowley
Shih-Fu Chang
43
47
0
12 Mar 2015
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
452
43,277
0
11 Feb 2015
Deep Fried Convnets
Deep Fried Convnets
Zichao Yang
Marcin Moczulski
Misha Denil
Nando de Freitas
Alex Smola
Le Song
Ziyu Wang
97
267
0
22 Dec 2014
In Search of the Real Inductive Bias: On the Role of Implicit
  Regularization in Deep Learning
In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning
Behnam Neyshabur
Ryota Tomioka
Nathan Srebro
AI4CE
90
657
0
20 Dec 2014
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
254
1,198
0
30 Nov 2014
Sequence to Sequence Learning with Neural Networks
Sequence to Sequence Learning with Neural Networks
Ilya Sutskever
Oriol Vinyals
Quoc V. Le
AIMat
421
20,541
0
10 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.6K
100,330
0
04 Sep 2014
Fastfood: Approximate Kernel Expansions in Loglinear Time
Fastfood: Approximate Kernel Expansions in Loglinear Time
Quoc V. Le
Tamás Sarlós
Alex Smola
89
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
121
230
0
21 Jul 2014
Identifying and attacking the saddle point problem in high-dimensional
  non-convex optimization
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization
Yann N. Dauphin
Razvan Pascanu
Çağlar Gülçehre
Kyunghyun Cho
Surya Ganguli
Yoshua Bengio
ODL
123
1,385
0
10 Jun 2014
On the Number of Linear Regions of Deep Neural Networks
On the Number of Linear Regions of Deep Neural Networks
Guido Montúfar
Razvan Pascanu
Kyunghyun Cho
Yoshua Bengio
88
1,254
0
08 Feb 2014
Do Deep Nets Really Need to be Deep?
Do Deep Nets Really Need to be Deep?
Lei Jimmy Ba
R. Caruana
162
2,117
0
21 Dec 2013
Compact Random Feature Maps
Compact Random Feature Maps
Raffay Hamid
Ying Xiao
Alex Gittens
D. DeCoste
73
87
0
17 Dec 2013
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
655
31,490
0
16 Jan 2013
Random Feature Maps for Dot Product Kernels
Random Feature Maps for Dot Product Kernels
Purushottam Kar
H. Karnick
75
256
0
31 Jan 2012
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