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Bayesian Neural Architecture Search using A Training-Free Performance
  Metric
v1v2 (latest)

Bayesian Neural Architecture Search using A Training-Free Performance Metric

29 January 2020
Andrés Camero
Hao Wang
Enrique Alba
Thomas Bäck
ArXiv (abs)PDFHTML

Papers citing "Bayesian Neural Architecture Search using A Training-Free Performance Metric"

13 / 13 papers shown
Title
Bayesian Optimization for Categorical and Category-Specific Continuous
  Inputs
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs
Dang Nguyen
Sunil R. Gupta
Santu Rana
A. Shilton
Svetha Venkatesh
118
50
0
28 Nov 2019
Random Error Sampling-based Recurrent Neural Network Architecture
  Optimization
Random Error Sampling-based Recurrent Neural Network Architecture Optimization
Andrés Camero
J. Toutouh
Enrique Alba
58
16
0
04 Sep 2019
Bayesian Optimization with Approximate Set Kernels
Bayesian Optimization with Approximate Set Kernels
Jungtaek Kim
M. McCourt
Tackgeun You
Saehoon Kim
Seungjin Choi
59
8
0
23 May 2019
Investigating Recurrent Neural Network Memory Structures using
  Neuro-Evolution
Investigating Recurrent Neural Network Memory Structures using Neuro-Evolution
Alexander Ororbia
A. ElSaid
Travis J. Desell
78
55
0
06 Feb 2019
DLOPT: Deep Learning Optimization Library
DLOPT: Deep Learning Optimization Library
Andrés Camero
J. Toutouh
Enrique Alba
ODL
56
7
0
10 Jul 2018
BIN-CT: Urban Waste Collection based in Predicting the Container Fill
  Level
BIN-CT: Urban Waste Collection based in Predicting the Container Fill Level
Javier Ferrer
Enrique Alba
43
37
0
03 Jul 2018
Low-Cost Recurrent Neural Network Expected Performance Evaluation
Low-Cost Recurrent Neural Network Expected Performance Evaluation
Andrés Camero
J. Toutouh
Enrique Alba
53
20
0
18 May 2018
Evolutionary Architecture Search For Deep Multitask Networks
Evolutionary Architecture Search For Deep Multitask Networks
J. Liang
Elliot Meyerson
Risto Miikkulainen
80
121
0
10 Mar 2018
Metaheuristic Design of Feedforward Neural Networks: A Review of Two
  Decades of Research
Metaheuristic Design of Feedforward Neural Networks: A Review of Two Decades of Research
Varun Ojha
Ajith Abraham
V. Snás̃el
95
498
0
16 May 2017
Evolving Deep Neural Networks
Evolving Deep Neural Networks
Risto Miikkulainen
J. Liang
Elliot Meyerson
Aditya Rawal
Daniel Fink
...
B. Raju
Hormoz Shahrzad
Arshak Navruzyan
Nigel P. Duffy
Babak Hodjat
101
890
0
01 Mar 2017
TensorFlow: A system for large-scale machine learning
TensorFlow: A system for large-scale machine learning
Martín Abadi
P. Barham
Jianmin Chen
Zhiwen Chen
Andy Davis
...
Vijay Vasudevan
Pete Warden
Martin Wicke
Yuan Yu
Xiaoqiang Zhang
GNNAI4CE
433
18,361
0
27 May 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.0K
150,312
0
22 Dec 2014
On the difficulty of training Recurrent Neural Networks
On the difficulty of training Recurrent Neural Networks
Razvan Pascanu
Tomas Mikolov
Yoshua Bengio
ODL
204
5,360
0
21 Nov 2012
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