Practical Bayesian Optimization of Machine Learning Algorithms

13 June 2012

Papers citing "Practical Bayesian Optimization of Machine Learning Algorithms"

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Title
Hyper-Parameter Optimization: A Review of Algorithms and Applications Tong Yu Hong Zhu AAML 21 522 0 12 Mar 2020
ENTMOOT: A Framework for Optimization over Ensemble Tree Models Alexander Thebelt Jan Kronqvist Miten Mistry Robert M. Lee Nathan Sudermann-Merx Ruth Misener 29 54 0 10 Mar 2020
Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time Hideaki Imamura Nontawat Charoenphakdee Futoshi Futami Issei Sato Junya Honda Masashi Sugiyama 33 3 0 10 Mar 2020
Cloth in the Wind: A Case Study of Physical Measurement through Simulation Tom F. H. Runia Kirill Gavrilyuk Cees G. M. Snoek A. Smeulders 19 28 0 09 Mar 2020
QTIP: Quick simulation-based adaptation of Traffic model per Incident Parameters Inon Peled R. Kamalakar Carlos Lima Azevedo Francisco Câmara Pereira 16 4 0 09 Mar 2020
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch Esteban Real Chen Liang David R. So Quoc V. Le 44 221 0 06 Mar 2020
Data-efficient Domain Randomization with Bayesian Optimization Fabio Muratore C. Eilers Michael Gienger Jan Peters OOD 78 78 0 05 Mar 2020
On Hyper-parameter Tuning for Stochastic Optimization Algorithms Haotian Zhang Jianyong Sun Zongben Xu 14 0 0 04 Mar 2020
Corruption-Tolerant Gaussian Process Bandit Optimization Ilija Bogunovic Andreas Krause Jonathan Scarlett 40 51 0 04 Mar 2020
Traversing the Reality Gap via Simulator Tuning J. Collins Ross Brown Jurgen Leitner David Howard 41 14 0 03 Mar 2020
Robust Policy Search for Robot Navigation Javier Garcia-Barcos Ruben Martinez-Cantin 21 3 0 02 Mar 2020
A Self-Tuning Actor-Critic Algorithm Tom Zahavy Zhongwen Xu Vivek Veeriah Matteo Hessel Junhyuk Oh H. V. Hasselt David Silver Satinder Singh 28 13 0 28 Feb 2020
Using a thousand optimization tasks to learn hyperparameter search strategies Luke Metz Niru Maheswaranathan Ruoxi Sun C. Freeman Ben Poole Jascha Narain Sohl-Dickstein 20 46 0 27 Feb 2020
Machine Learning based prediction of noncentrosymmetric crystal materials Yuqi Song Joseph Lindsay Yong Zhao Alireza Nasiri Steph-Yves M. Louis Jie Ling Ming Hu Jianjun Hu 25 21 0 26 Feb 2020
Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling Cheng Li Sunil R. Gupta Santu Rana Vu Nguyen A. Robles-Kelly Svetha Venkatesh 10 15 0 26 Feb 2020
Efficient Rollout Strategies for Bayesian Optimization E. Lee David Eriksson Bolong Cheng M. McCourt D. Bindel 21 24 0 24 Feb 2020
Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting Niccolò Dalmasso Rafael Izbicki Ann B. Lee 22 20 0 24 Feb 2020
Predictive intraday correlations in stable and volatile market environments: Evidence from deep learning Ben Moews Gbenga Ibikunle AIFin 9 15 0 24 Feb 2020
Practical Bayesian Optimization of Objectives with Conditioning Variables Michael Pearce Janis Klaise Matthew J. Groves 26 1 0 23 Feb 2020
Weighting Is Worth the Wait: Bayesian Optimization with Importance Sampling Setareh Ariafar Zelda E. Mariet Ehsan Elhamifar Dana Brooks Jennifer Dy Jasper Snoek 14 3 0 23 Feb 2020
Efficiently Sampling Functions from Gaussian Process Posteriors James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 16 163 0 21 Feb 2020
Implicit differentiation of Lasso-type models for hyperparameter optimization Quentin Bertrand Quentin Klopfenstein Mathieu Blondel Samuel Vaiter Alexandre Gramfort Joseph Salmon 40 64 0 20 Feb 2020
Do We Need Zero Training Loss After Achieving Zero Training Error? Takashi Ishida Ikko Yamane Tomoya Sakai Gang Niu Masashi Sugiyama AI4CE 49 135 0 20 Feb 2020
Scalable Constrained Bayesian Optimization David Eriksson Matthias Poloczek 35 96 0 20 Feb 2020
Online Parameter Estimation for Safety-Critical Systems with Gaussian Processes Mouhyemen Khan A. Chatterjee 6 0 0 18 Feb 2020
Learning Adaptive Loss for Robust Learning with Noisy Labels Jun Shu Qian Zhao Keyu Chen Zongben Xu Deyu Meng NoLa OOD 19 23 0 16 Feb 2020
Multi-Task Multicriteria Hyperparameter Optimization Kirill Akhmetzyanov A. Yuzhakov 6 3 0 15 Feb 2020
Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription Olivier Francon Santiago Gonzalez B. Hodjat Elliot Meyerson Risto Miikkulainen Xin Qiu H. Shahrzad 26 16 0 13 Feb 2020
Regret Bounds for Noise-Free Kernel-Based Bandits Sattar Vakili 41 3 0 12 Feb 2020
Learning to Compare for Better Training and Evaluation of Open Domain Natural Language Generation Models Wangchunshu Zhou Ke Xu ELM ALM 14 43 0 12 Feb 2020
Computing the racing line using Bayesian optimization Achin Jain M. Morari 37 33 0 12 Feb 2020
Debugging Machine Learning Pipelines Raoni Lourenço J. Freire D. Shasha AI4CE 21 28 0 11 Feb 2020
Regularized Evolutionary Population-Based Training J. Liang Santiago Gonzalez H. Shahrzad Risto Miikkulainen 22 9 0 11 Feb 2020
A Physiology-Driven Computational Model for Post-Cardiac Arrest Outcome Prediction Hanbiehn Kim Hieu Nguyen Qingchu Jin Sharmila Tamby Tatiana Gelaf Romer ... J. Greenstein J. Suarez C. Storm R. Winslow R. Stevens 39 6 0 09 Feb 2020
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits Jack Parker-Holder Vu Nguyen Stephen J. Roberts OffRL 75 83 0 06 Feb 2020
$ε$ -shotgun: $ε$ -greedy Batch Bayesian Optimisation George De Ath Richard Everson J. Fieldsend Alma A. M. Rahat 29 15 0 05 Feb 2020
BOFFIN TTS: Few-Shot Speaker Adaptation by Bayesian Optimization Henry B. Moss Vatsal Aggarwal N. Prateek Javier I. González Roberto Barra-Chicote BDL 14 57 0 04 Feb 2020
Automatic Pruning for Quantized Neural Networks Luis Guerra Bohan Zhuang Ian Reid Tom Drummond MQ 22 21 0 03 Feb 2020
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization Benjamin Letham Roberto Calandra Akshara Rai E. Bakshy 78 111 0 31 Jan 2020
Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness George Wynne F. Briol Mark Girolami 27 56 0 29 Jan 2020
Reservoir computing model of two-dimensional turbulent convection S. Pandey J. Schumacher 27 40 0 28 Jan 2020
Feature selection in machine learning: Rényi min-entropy vs Shannon entropy C. Palamidessi Marco Romanelli 13 2 0 27 Jan 2020
Bayesian optimization for backpropagation in Monte-Carlo tree search Yueqin Li Nengli Lim BDL 6 0 0 25 Jan 2020
Tuneful: An Online Significance-Aware Configuration Tuner for Big Data Analytics Ayat Fekry Lucian Carata Thomas Pasquier Andrew Rice A. Hopper 45 16 0 22 Jan 2020
AutoFCL: Automatically Tuning Fully Connected Layers for Handling Small Dataset S. H. Shabbeer Basha Sravan Kumar Vinakota S. Dubey Viswanath Pulabaigari Snehasis Mukherjee 19 4 0 22 Jan 2020
Zeroth-Order Algorithms for Nonconvex Minimax Problems with Improved Complexities Zhongruo Wang Krishnakumar Balasubramanian Shiqian Ma Meisam Razaviyayn 26 25 0 22 Jan 2020
Learning Directed Locomotion in Modular Robots with Evolvable Morphologies Gongjin Lan Matteo De Carlo Fuda van Diggelen Jakub M. Tomczak D. Roijers A. E. Eiben 29 49 0 21 Jan 2020
Traffic Data Imputation using Deep Convolutional Neural Networks O. Benkraouda Bilal Thonnam Thodi H. Yeo M. Menéndez Saif Eddin Jabari 11 28 0 21 Jan 2020
Bayesian Optimization for Policy Search in High-Dimensional Systems via Automatic Domain Selection Lukas P. Frohlich Edgar D. Klenske Christian Daniel Melanie Zeilinger 18 12 0 21 Jan 2020
Active Learning over DNN: Automated Engineering Design Optimization for Fluid Dynamics Based on Self-Simulated Dataset Yang Chen AI4CE 11 2 0 18 Jan 2020