, TensorFlow: Large-scale machine learning on heterogeneous systems, 2015. Software available from tensorflow.org, vol.2, p.5
Efficient architecture search by network transformation. The Thirty-Second AAAI Conferenceon Artificial Intelligence, 2018. ,
learningcompression algorithms for neural net pruning, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.8532-8541, 2018. ,
Particle Swarm Model Selection, Journal of Machine Learning Research, vol.10, issue.3, pp.405-440, 2009. ,
Efficient and robust automated machine learning, Advances in Neural Information Processing Systems, vol.28, pp.2962-2970, 2015. ,
Design of the 2015 ChaLearn AutoML challenge, vol.5, p.6, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01381164
A Brief Review of the ChaLearn AutoML Challenge: Any-time Anydataset Learning Without Human Intervention, Workshop on Automatic Machine Learning, vol.5, p.6, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01381145
Analysis of the automl challenge series, vol.2, p.5, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01906197
Identity mappings in deep residual networks, European conference on computer vision, vol.8, p.9, 2016. ,
Improving neural networks by preventing co-adaptation of feature detectors, 2012. ,
Adam: A Method for Stochastic Optimization, 2014. ,
A Study of Cross-validation and Bootstrap for Accuracy Estimation and Model Selection, Proceedings of the 14th International Joint Conference on Artificial Intelligence, vol.2, pp.1137-1143, 1995. ,
Progressive neural architecture search, The European Conference on Computer Vision (ECCV), 2004. ,
AutoDL Challenge Design and Beta Tests-Towards automatic deep learning, MetaLearn workshop @ NIPS2018, 2005. ,
URL : https://hal.archives-ouvertes.fr/hal-01906226
Autonomous deep learning: A genetic DCNN designer for image classification, 2018. ,
Blockout: Dynamic model selection for hierarchical deep networks, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.2583-2591, 2004. ,
Automatic differentiation in pytorch, 2017. ,
Scikit-learn: Machine Learning in Python, Journal of Machine Learning Research, vol.12, issue.2, pp.2825-2830, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00650905
Efficient progressive neural architecture search, 2018. ,
Efficient neural architecture search via parameters sharing, Proceedings of the 35th International Conference on Machine Learning, vol.80, pp.10-15, 2018. ,
Rethinking the Inception Architecture for Computer Vision, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol.8, p.9, 2016. ,
, Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms, 2012.
Hd-cnn: Hierarchical deep convolutional neural networks for large scale visual recognition, The IEEE International Conference on Computer Vision (ICCV), pp.2740-2748, 2004. ,