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On tuning deep learning models: a data mining perspective

On tuning deep learning models: a data mining perspective

19 November 2020
M. Öztürk
ArXivPDFHTML

Papers citing "On tuning deep learning models: a data mining perspective"

31 / 31 papers shown
Title
Impact of Data Normalization on Deep Neural Network for Time Series
  Forecasting
Impact of Data Normalization on Deep Neural Network for Time Series Forecasting
Samit Bhanja
Abhishek Das
AI4TS
14
90
0
13 Dec 2018
Deep learning for time series classification: a review
Deep learning for time series classification: a review
Hassan Ismail Fawaz
Germain Forestier
J. Weber
L. Idoumghar
Pierre-Alain Muller
AI4TS
AI4CE
208
2,668
0
12 Sep 2018
Understanding Batch Normalization
Understanding Batch Normalization
Johan Bjorck
Carla P. Gomes
B. Selman
Kilian Q. Weinberger
72
603
0
01 Jun 2018
How Does Batch Normalization Help Optimization?
How Does Batch Normalization Help Optimization?
Shibani Santurkar
Dimitris Tsipras
Andrew Ilyas
Aleksander Madry
ODL
56
1,531
0
29 May 2018
Generalized Cross Entropy Loss for Training Deep Neural Networks with
  Noisy Labels
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels
Zhilu Zhang
M. Sabuncu
NoLa
50
2,580
0
20 May 2018
Hyperparameters and Tuning Strategies for Random Forest
Hyperparameters and Tuning Strategies for Random Forest
Philipp Probst
Marvin N. Wright
A. Boulesteix
103
1,375
0
10 Apr 2018
Hessian-based Analysis of Large Batch Training and Robustness to
  Adversaries
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries
Z. Yao
A. Gholami
Qi Lei
Kurt Keutzer
Michael W. Mahoney
46
166
0
22 Feb 2018
The Effectiveness of Data Augmentation in Image Classification using
  Deep Learning
The Effectiveness of Data Augmentation in Image Classification using Deep Learning
Luis Perez
Jason Wang
46
2,771
0
13 Dec 2017
Don't Decay the Learning Rate, Increase the Batch Size
Don't Decay the Learning Rate, Increase the Batch Size
Samuel L. Smith
Pieter-Jan Kindermans
Chris Ying
Quoc V. Le
ODL
73
990
0
01 Nov 2017
A Bayesian Data Augmentation Approach for Learning Deep Models
A Bayesian Data Augmentation Approach for Learning Deep Models
Toan M. Tran
Trung T. Pham
G. Carneiro
L. Palmer
Ian Reid
46
233
0
29 Oct 2017
Improving Deep Learning using Generic Data Augmentation
Improving Deep Learning using Generic Data Augmentation
Luke Taylor
G. Nitschke
25
383
0
20 Aug 2017
An effective algorithm for hyperparameter optimization of neural
  networks
An effective algorithm for hyperparameter optimization of neural networks
G. I. Diaz
Achille Fokoue
G. Nannicini
Horst Samulowitz
34
156
0
23 May 2017
Learning Deep Visual Object Models From Noisy Web Data: How to Make it
  Work
Learning Deep Visual Object Models From Noisy Web Data: How to Make it Work
Nizar Massouh
F. Babiloni
Tatiana Tommasi
Jay Young
Nick Hawes
Barbara Caputo
VLM
25
17
0
28 Feb 2017
Learning the Number of Neurons in Deep Networks
Learning the Number of Neurons in Deep Networks
J. Álvarez
Mathieu Salzmann
89
413
0
19 Nov 2016
Deep Convolutional Neural Networks and Data Augmentation for
  Environmental Sound Classification
Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification
Justin Salamon
J. P. Bello
40
1,300
0
15 Aug 2016
Efficient Hyperparameter Optimization of Deep Learning Algorithms Using
  Deterministic RBF Surrogates
Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates
Ilija Ilievski
Taimoor Akhtar
Jiashi Feng
C. Shoemaker
34
150
0
28 Jul 2016
Learning to Track at 100 FPS with Deep Regression Networks
Learning to Track at 100 FPS with Deep Regression Networks
David Held
Sebastian Thrun
Silvio Savarese
OffRL
53
1,190
0
06 Apr 2016
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
Lisha Li
Kevin Jamieson
Giulia DeSalvo
Afshin Rostamizadeh
Ameet Talwalkar
135
2,307
0
21 Mar 2016
A Light CNN for Deep Face Representation with Noisy Labels
A Light CNN for Deep Face Representation with Noisy Labels
Xiang Wu
Ran He
Zhenan Sun
Tieniu Tan
CVBM
58
1,064
0
09 Nov 2015
Layer-Specific Adaptive Learning Rates for Deep Networks
Layer-Specific Adaptive Learning Rates for Deep Networks
Bharat Singh
Soham De
Yangmuzi Zhang
Thomas A. Goldstein
Gavin Taylor
ODL
AI4CE
42
71
0
15 Oct 2015
Batch Normalized Recurrent Neural Networks
Batch Normalized Recurrent Neural Networks
César Laurent
Gabriel Pereyra
Philemon Brakel
Yanzhe Zhang
Yoshua Bengio
47
213
0
05 Oct 2015
Variational Dropout and the Local Reparameterization Trick
Variational Dropout and the Local Reparameterization Trick
Diederik P. Kingma
Tim Salimans
Max Welling
BDL
118
1,500
0
08 Jun 2015
Cyclical Learning Rates for Training Neural Networks
Cyclical Learning Rates for Training Neural Networks
L. Smith
ODL
92
2,515
0
03 Jun 2015
Enhanced Higgs to $τ^+τ^-$ Searches with Deep Learning
Enhanced Higgs to τ+τ−τ^+τ^-τ+τ− Searches with Deep Learning
Pierre Baldi
Peter Sadowski
D. Whiteson
26
94
0
13 Oct 2014
OpenML: networked science in machine learning
OpenML: networked science in machine learning
Joaquin Vanschoren
Jan N. van Rijn
B. Bischl
Luís Torgo
FedML
AI4CE
62
1,310
0
29 Jul 2014
Training Convolutional Networks with Noisy Labels
Training Convolutional Networks with Noisy Labels
Sainbayar Sukhbaatar
Joan Bruna
Manohar Paluri
Lubomir D. Bourdev
Rob Fergus
NoLa
45
270
0
09 Jun 2014
Deep Learning in Neural Networks: An Overview
Deep Learning in Neural Networks: An Overview
Jürgen Schmidhuber
HAI
132
16,311
0
30 Apr 2014
PCANet: A Simple Deep Learning Baseline for Image Classification?
PCANet: A Simple Deep Learning Baseline for Image Classification?
Tsung-Han Chan
Kui Jia
Shenghua Gao
Jiwen Lu
Zinan Zeng
Yi-An Ma
88
1,496
0
14 Apr 2014
Dropout improves Recurrent Neural Networks for Handwriting Recognition
Dropout improves Recurrent Neural Networks for Handwriting Recognition
Vu Pham
Théodore Bluche
Christopher Kermorvant
J. Louradour
63
566
0
05 Nov 2013
Speech Recognition with Deep Recurrent Neural Networks
Speech Recognition with Deep Recurrent Neural Networks
Alex Graves
Abdel-rahman Mohamed
Geoffrey E. Hinton
99
8,503
0
22 Mar 2013
ADADELTA: An Adaptive Learning Rate Method
ADADELTA: An Adaptive Learning Rate Method
Matthew D. Zeiler
ODL
74
6,619
0
22 Dec 2012
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