Awesome
Awesome Architecture Search ![Awesome](https://awesome.re/badge.svg)
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<img width="250" src="https://camo.githubusercontent.com/1131548cf666e1150ebd2a52f44776d539f06324/68747470733a2f2f63646e2e7261776769742e636f6d2f73696e647265736f726875732f617765736f6d652f6d61737465722f6d656469612f6c6f676f2e737667" "Awesome!">
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A curated list of awesome architecture search and hyper-parameter optimization resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning and awesome-deep-learning-papers.
Hyper-parameter optimization has always been a popular field in the Machine Learning community, architecture search just emerges as a rising star in recent years. These are some of the awesome resources!
Table of Contents
Architecture Search
Reinforcement Learning
- Neural Architecture Search with Reinforcement Learning [pdf]
- Barret Zoph and Quoc V. Le. ICLR'17
- Designing Neural Network Architectures Using Reinforcement Learning [pdf] [code]
- Bowen Baker, Otkrist Gupta, Nikhil Naik, Ramesh Raskar. ICLR'17
- Efficient Architecture Search by Network Transformation [pdf] [code]
- Han Cai, Tianyao Chen, Weinan Zhang, Yong Yu, Jun Wang. AAAI'18
- Learning Transferable Architectures for Scalable Image Recognition [pdf] [nasnet]
- Barret Zoph, Vijay Vasudevan, Jonathan Shlens, Quoc V. Le. Arxiv 1707
- Practical Block-wise Neural Network Architecture Generation [pdf]
- Zhao Zhong, Junjie Yan, Wei Wu, Jing Shao, Cheng-Lin Liu. CVPR'18
- A Flexible Approach to Automated RNN Architecture Generation [pdf]
- Martin Schrimpf, Stephen Merity, James Bradbury, Richard Socher. ICLR'18
- Efficient Neural Architecture Search via Parameter Sharing [pdf] [code (not official)] [code (official)]
- Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, Jeff Dean. Arxiv 1802
- Path-Level Network Transformation for Efficient Architecture Search [pdf] [code]
- Han Cai, Jiacheng Yang, Weinan Zhang, Song Han, Yong Yu. ICML'18
Evolutionary Algorithm
- Large-Scale Evolution of Image Classifiers [pdf]
- Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Jie Tan, Quoc Le, Alex Kurakin. ICML'17
- Genetic CNN [pdf] [code]
- Lingxi Xie and Alan Yuille. ICCV'17
- Hierarchical Representations for Efficient Architecture Search [pdf]
- Hanxiao Liu, Karen Simonyan, Oriol Vinyals, Chrisantha Fernando, Koray Kavukcuoglu. ICLR'18
- Regularized Evolution for Image Classifier Architecture Search [pdf]
- Esteban Real, Alok Aggarwal, Yanping Huang, Quoc V Le. Arxiv 1802
- Weight Agnostic Neural Networks [pdf]
- Adam Gaier, David Ha. NeurIPS'19
Others
- Neural Architecture Optimization [pdf] [code]
- Renqian Luo, Fei Tian, Tao Qin, Enhong Chen, Tie-Yan Liu. Arxiv 1808
- DeepArchitect: Automatically Designing and Training Deep Architectures [pdf] [code]
- Renato Negrinho and Geoff Gordon. Arxiv 1704
- SMASH: One-Shot Model Architecture Search through HyperNetworks [pdf] [code]
- Andrew Brock, Theodore Lim, J.M. Ritchie, Nick Weston. ICLR'18
- Simple and efficient architecture search for Convolutional Neural Networks [pdf]
- Thomas Elsken, Jan-Hendrik Metzen, Frank Hutter. ICLR'18 Workshop
- Progressive Neural Architecture Search [pdf]
- Chenxi Liu, Barret Zoph, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan Yuille, Jonathan Huang, Kevin Murphy. Arxiv 1712
- DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures [pdf]
- Jin-Dong Dong, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun. ECCV'18
- Neural Architecture Search with Bayesian Optimisation and Optimal Transport [pdf]
- Kirthevasan Kandasamy, Willie Neiswanger, Jeff Schneider, Barnabas Poczos, Eric Xing. Arxiv 1802
- Effective Building Block Design for Deep Convolutional Neural Networks using Search [pdf]
- Jayanta K Dutta, Jiayi Liu, Unmesh Kurup, Mohak Shah. Arxiv 1801
- DARTS: Differentiable Architecture Search [pdf] [code]
- Hanxiao Liu, Karen Simonyan, Yiming Yang. Arxiv 1806
- Efficient Neural Architecture Search with Network Morphism [pdf] [code]
- Haifeng Jin, Qingquan Song, Xia Hu. Arxiv 1806
- Searching for Efficient Multi-Scale Architectures for Dense Image Prediction [pdf]
- Liang-Chieh Chen, Maxwell D. Collins, Yukun Zhu, George Papandreou, Barret Zoph, Florian Schroff, Hartwig Adam, Jonathon Shlens. Arxiv 1809
- AMC: AutoML for Model Compression and Acceleration on Mobile Devices [pdf] [code (not official)]
- Yihui He, Ji Lin, Zhijian Liu, Hanrui Wang, Li-Jia Li, Song Han. ECCV'18
- MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks [pdf]
- Ariel Gordon, Elad Eban, Bo Chen, Ofir Nachum, Tien-Ju Yang, Edward Choi. CVPR'18
- Weight Agnostic Neural Networks [pdf]
- Adam Gaier, David Ha. NeurIPS'19
- Towards Modular and Programmable Architecture Search [pdf] [code]
- Renato Negrinho, Darshan Patil, Nghia Le, Daniel Ferreira, Matthew Gormley, Geoffrey Gordon. NeurIPS'19
Hyper-Parameter Search
- Speeding up Automatic Hyperparameter Optimization of Deep Neural Networksby Extrapolation of Learning Curves [pdf] [code]
- Tobias Domhan, Jost Tobias Springenberg, Frank Hutter. IJCAI'15
- Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization [pdf]
- Lisha Li, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar. ICLR'17
- Learning Curve Prediction with Bayesian Neural Networks [pdf]
- Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter. ICLR'17
- Accelerating Neural Architecture Search using Performance Prediction [pdf]
- Bowen Baker, Otkrist Gupta, Ramesh Raskar, Nikhil Naik. ICLR'18 Workshop
- Hyperparameter Optimization: A Spectral Approach [pdf] [code]
- Elad Hazan, Adam Klivans, Yang Yuan. NIPS DLTP Workshop 2017
- Population Based Training of Neural Networks [pdf]
- Max Jaderberg, Valentin Dalibard, Simon Osindero, Wojciech M. Czarnecki, Jeff Donahue, Ali Razavi, Oriol Vinyals, Tim Green, Iain Dunning, Karen Simonyan, Chrisantha Fernando, Koray Kavukcuoglu. Arxiv 1711
Contributing
<p align="center"> <img src="http://cdn1.sportngin.com/attachments/news_article/7269/5172/needyou_small.jpg" alt="We Need You!"> </p>Please help contribute this list by contacting me or add pull request
Markdown format:
- Paper Name [[pdf]](link) [[code]](link)
- Author 1, Author 2, Author 3. *Conference'Year*
License
To the extent possible under law, Mark Dong has waived all copyright and related or neighboring rights to this work.