Simple And Efficient Architecture Search for Convolutional Neural Networks

Artificial Intelligence: A Modern Approach (3rd Edition)

Stuart Russell and Peter Norvig · 2009

Earlier work this paper cites.

Algorithms for hyper-parameter optimization

J. Bergstra, R. Bardenet, Y. Bengio, and B. Kégl · 2011

Earlier work this paper cites.

Random search for hyper-parameter optimization

J. Bergstra and Y. Bengio · 2012

Earlier work this paper cites.

Deep neural networks for acoustic modeling in speech recognition

Geoffrey Hinton, Li Deng, Dong Yu, George Dahl, Abdel rahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Tara Sainath, and Brian Kingsbury · 2012

Earlier work this paper cites.

Imagenet classification with deep convolutional neural networks

Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012

Earlier work this paper cites.

Practical Bayesian optimization of machine learning algorithms

J. Snoek, H. Larochelle, and R.P. Adams · 2012

Earlier work this paper cites.

TensorFlow: Large-scale machine learning on heterogeneous systems, 2015

Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015

Earlier work this paper cites.

Neural machine translation by jointly learning to align and translate

Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2015

Earlier work this paper cites.

Net2net: Accelerating learning via knowledge transfer

Tianqi Chen, Ian J. Goodfellow, and Jonathon Shlens · 2015

Earlier work this paper cites.

Designing neural network architectures using reinforcement learning

Bowen Baker, Otkrist Gupta, Nikhil Naik, and Ramesh Raskar · 2016

Earlier work this paper cites.

Deep residual learning for image recognition

Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016

Cited alongside, same era.

Densely connected convolutional networks

Gao Huang, Zhuang Liu, and Kilian Q. Weinberger · 2016

Cited alongside, same era.

CMA-ES for hyperparameter optimization of deep neural networks

Original

I. Loshchilov and F. Hutter · 2016

Cited alongside, same era.

Towards automatically-tuned neural networks

H. Mendoza, A. Klein, M. Feurer, T. Springenberg, and F. Hutter · 2016

Cited alongside, same era.

Convolutional neural fabrics

Shreyas Saxena and Jakob Verbeek · 2016

Cited alongside, same era.

Network morphism

Tao Wei, Changhu Wang, Yong Rui, and Chang Wen Chen · 2016

Cited alongside, same era.

Shake-shake regularization

Xavier Gastaldi · 2017

Closest in time.

Hypernetworks

David Ha, Andrew M. Dai, and Quoc V. Le · 2017

Closest in time.

Snapshot ensembles: Train 1, get M for free

Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, and Kilian Q. Weinberger · 2017

Closest in time.

Learning curve prediction with Bayesian neural networks

A. Klein, S. Falkner, J. T. Springenberg, and F. Hutter · 2017

Closest in time.

Sgdr: Stochastic gradient descent with warm restarts

I. Loshchilov and F. Hutter · 2017

Closest in time.

Large-scale evolution of image classifiers

Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Quoc V. Le, and Alex Kurakin · 2017

Closest in time.