AutoML方向 博士毕业论文汇总

原文: http://zhuanlan.zhihu.com/p/569902591

AutoML（Automated Machine Learning，自动机器学习）大火应该是从2016年谷歌的一篇NAS工作开始的，到今天AutoML也到了一个阶段性的成果收获季节了，因为陆续有这个方向的博士毕业了，下面总结了AutoML方向的博士毕业论文，仅供参考。

• Efficient Neural Networks
• Parallel and Distributed Methods for Autonomous Design of Artificial Neural Networks
• Efficient neural architectures for edge devices Supervisors
• Evolving Deep Neural Network Architectures for Time Series Data
• Automated Machine Learning Under Resource Constraints
• Towards Efficient Deep Neural Networks
• Automated Deep Learning: Principles and Practice
• From Human-Designed Convolutional Neural Networks Towards Robust Neural Architecture Search
• The Nonlinearity Coefficient - A Practical Guide to Neural Architecture Design
• Efficient Neural Architecture Search for Automated Deep Learning
• Efficient and Generalizable Neural Architecture Search for Visual Recognition
• Relaxation and Optimization for Automated Learning of Neural Network Architectures

资料参考自 https://www.ml4aad.org/automl/literature-on-neural-architecture-search/