A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

12 December 2010

Papers citing "A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning"

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DarwinML: A Graph-based Evolutionary Algorithm for Automated Machine Learning Fei Qi Z. Xia Gaoyang Tang Hang Yang Yu Song Guangrui Qian Xiong An Chunhuan Lin Guangming Shi AI4CE 45 5 0 20 Nov 2018
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Using Known Information to Accelerate HyperParameters Optimization Based on SMBO Daning Cheng Hanping Zhang Xia Fen Shigang Li Yunquan Zhang 22 0 0 08 Nov 2018
Practical Batch Bayesian Optimization for Less Expensive Functions Vu Nguyen Sunil R. Gupta Santu Rana Cheng Li Svetha Venkatesh 34 3 0 05 Nov 2018
Democratizing Production-Scale Distributed Deep Learning Minghuang Ma Hadi Pouransari Daniel Chao Saurabh N. Adya S. Serrano Yi Qin Dan Gimnicher Dominic Walsh MoE 110 6 0 31 Oct 2018
Machine Learning Accelerated Likelihood-Free Event Reconstruction in Dark Matter Direct Detection U. Simola B. Pelssers D. Barge J. Conrad J. Corander 144 11 0 23 Oct 2018
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Identifying Bias in AI using Simulation Daniel J. McDuff R. Cheng Ashish Kapoor 58 22 0 30 Sep 2018
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks Kenneth T. Co Luis Muñoz-González Sixte de Maupeou Emil C. Lupu AAML 74 67 0 30 Sep 2018
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A new Taxonomy of Continuous Global Optimization Algorithms Jörg Stork A. E. Eiben Thomas Bartz-Beielstein 63 33 0 27 Aug 2018
Active Learning based on Data Uncertainty and Model Sensitivity Nutan Chen Alexej Klushyn A. Paraschos Djalel Benbouzid Patrick van der Smagt 72 17 0 06 Aug 2018
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Neural-net-induced Gaussian process regression for function approximation and PDE solution G. Pang Liu Yang George Karniadakis 78 73 0 22 Jun 2018