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[1] Zhuowen Tu,et al. Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree , 2015, AISTATS.
[2] Jasper Snoek,et al. Multi-Task Bayesian Optimization , 2013, NIPS.
[3] Xinyun Chen. Under Review as a Conference Paper at Iclr 2017 Delving into Transferable Adversarial Ex- Amples and Black-box Attacks , 2016 .
[4] David D. Cox,et al. Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures , 2013, ICML.
[5] Risto Miikkulainen,et al. Evolving Neural Networks through Augmenting Topologies , 2002, Evolutionary Computation.
[6] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[7] Andrew W. Moore,et al. Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..
[8] Nando de Freitas,et al. Taking the Human Out of the Loop: A Review of Bayesian Optimization , 2016, Proceedings of the IEEE.
[9] Yann LeCun,et al. Pedestrian Detection with Unsupervised Multi-stage Feature Learning , 2012, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[10] Yann LeCun,et al. Convolutional neural networks applied to house numbers digit classification , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).
[11] Jakob Verbeek,et al. Convolutional Neural Fabrics , 2016, NIPS.
[12] Dimitri P. Bertsekas,et al. Convex Optimization Algorithms , 2015 .
[13] Yoshua Bengio,et al. Maxout Networks , 2013, ICML.
[14] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[15] Qiang Chen,et al. Network In Network , 2013, ICLR.
[16] Yann LeCun,et al. Regularization of Neural Networks using DropConnect , 2013, ICML.
[17] Mehryar Mohri,et al. Multi-armed Bandit Algorithms and Empirical Evaluation , 2005, ECML.
[18] Sepp Hochreiter,et al. Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) , 2015, ICLR.
[19] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[20] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[21] Robert Babuska,et al. Experience Replay for Real-Time Reinforcement Learning Control , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[22] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[23] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[24] Yoshua Bengio,et al. Algorithms for Hyper-Parameter Optimization , 2011, NIPS.
[25] Xiaolin Hu,et al. Recurrent convolutional neural network for object recognition , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[27] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[28] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[29] Josh Harguess,et al. Generative NeuroEvolution for Deep Learning , 2013, ArXiv.
[30] J. D. Schaffer,et al. Combinations of genetic algorithms and neural networks: a survey of the state of the art , 1992, [Proceedings] COGANN-92: International Workshop on Combinations of Genetic Algorithms and Neural Networks.
[31] G. D. Magoulas,et al. Under review as a conference paper at ICLR 2017 , 2022 .
[32] Jian Sun,et al. Identity Mappings in Deep Residual Networks , 2016, ECCV.
[33] Frank Hutter,et al. Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves , 2015, IJCAI.
[34] Omer Levy,et al. Published as a conference paper at ICLR 2018 S IMULATING A CTION D YNAMICS WITH N EURAL P ROCESS N ETWORKS , 2018 .
[35] Jasper Snoek,et al. Practical Bayesian Optimization of Machine Learning Algorithms , 2012, NIPS.
[36] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[37] Ben J. A. Kröse,et al. Learning from delayed rewards , 1995, Robotics Auton. Syst..
[38] Long-Ji Lin,et al. Reinforcement learning for robots using neural networks , 1992 .
[39] David D. Cox,et al. A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation , 2009, PLoS Comput. Biol..
[40] Yoshua Bengio,et al. FitNets: Hints for Thin Deep Nets , 2014, ICLR.
[41] Long Ji Lin,et al. Self-improving reactive agents based on reinforcement learning, planning and teaching , 1992, Machine Learning.
[42] Thomas Brox,et al. Striving for Simplicity: The All Convolutional Net , 2014, ICLR.