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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Bayesian Active Learning for Structured Output Design Kota Matsui Shunya Kusakawa Keisuke Ando Kentaro Kutsukake T. Ujihara Ichiro Takeuchi 21 6 0 09 Nov 2019
A Programmable Approach to Neural Network Compression Vinu Joseph Saurav Muralidharan Animesh Garg M. Garland Ganesh Gopalakrishnan 66 10 0 06 Nov 2019
Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation Viet Anh Nguyen Soroosh Shafieezadeh-Abadeh Man-Chung Yue Daniel Kuhn W. Wiesemann 69 29 0 23 Oct 2019
Dynamic Subgoal-based Exploration via Bayesian Optimization Yijia Wang Matthias Poloczek Daniel R. Jiang 78 3 0 21 Oct 2019
Parameter Optimization and Learning in a Spiking Neural Network for UAV Obstacle Avoidance targeting Neuromorphic Processors Llewyn Salt David Howard Giacomo Indiveri Yulia Sandamirskaya 42 46 0 17 Oct 2019
Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization Viet Anh Nguyen Soroosh Shafieezadeh-Abadeh Man-Chung Yue Daniel Kuhn W. Wiesemann 31 23 0 17 Oct 2019
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation Marko Jarvenpaa Aki Vehtari Pekka Marttinen 70 15 0 14 Oct 2019
Deep Kernels with Probabilistic Embeddings for Small-Data Learning Ankur Mallick Chaitanya Dwivedi B. Kailkhura Gauri Joshi T. Y. Han BDL UQCV 53 8 0 13 Oct 2019
Bayesian Optimization using Pseudo-Points Chao Qian Hang Xiong Ke Xue 62 15 0 12 Oct 2019
Evolving Gaussian Process kernels from elementary mathematical expressions Ibai Roman Roberto Santana A. Mendiburu Jose A. Lozano 44 3 0 11 Oct 2019
Attacking Vision-based Perception in End-to-End Autonomous Driving Models Adith Boloor Karthik Garimella Xin He C. Gill Yevgeniy Vorobeychik Xuan Zhang AAML 80 108 0 02 Oct 2019
Active preference learning based on radial basis functions Alberto Bemporad Dario Piga 61 9 0 28 Sep 2019
Bayesian Optimization for Iterative Learning Vu-Linh Nguyen Sebastian Schulze Michael A. Osborne BDL 114 33 0 20 Sep 2019
Efficient Transfer Bayesian Optimization with Auxiliary Information Tomoharu Iwata Takuma Otsuka 71 2 0 17 Sep 2019
Bayesian Optimization under Heavy-tailed Payoffs Sayak Ray Chowdhury Aditya Gopalan 65 27 0 16 Sep 2019
Surrogate-based Optimization using Mutual Information for Computer Experiments (optim-MICE) Theodoros Mathikolonis S. Guillas 47 3 0 10 Sep 2019
Cost-aware Multi-objective Bayesian optimisation Majid Abdolshah A. Shilton Santu Rana Sunil R. Gupta Svetha Venkatesh 56 18 0 09 Sep 2019
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ConfigTron: Tackling network diversity with heterogeneous configurations Usama Naseer Theophilus A. Benson 26 13 0 13 Aug 2019
Automatic Calibration of Dynamic and Heterogeneous Parameters in Agent-based Model Dongjun Kim Tae-Sub Yun Il-Chul Moon 13 3 0 09 Aug 2019
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations Ksenia Korovina Sailun Xu Kirthevasan Kandasamy Willie Neiswanger Barnabás Póczós J. Schneider Eric Xing 123 123 0 05 Aug 2019
No-PASt-BO: Normalized Portfolio Allocation Strategy for Bayesian Optimization Thiago de P. Vasconcelos Daniel Augusto R. M. A. de Souza C. L. C. Mattos Joao P. P. Gomes 46 12 0 01 Aug 2019
pySOT and POAP: An event-driven asynchronous framework for surrogate optimization David Eriksson D. Bindel C. Shoemaker 75 57 0 30 Jul 2019
Adaptive Compression-based Lifelong Learning Shivangi Srivastava Maxim Berman Matthew B. Blaschko D. Tuia CLL 77 10 0 23 Jul 2019
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Automated Machine Learning in Practice: State of the Art and Recent Results Lukas Tuggener Mohammadreza Amirian Katharina Rombach Stefan Lörwald Anastasia Varlet Christian Westermann Thilo Stadelmann 46 65 0 19 Jul 2019
Meta-Learning for Black-box Optimization T. Vishnu Pankaj Malhotra Jyoti Narwariya Lovekesh Vig Gautam M. Shroff 62 19 0 16 Jul 2019
Robust Humanoid Locomotion Using Trajectory Optimization and Sample-Efficient Learning Mohammad Hasan Yeganegi Majid Khadiv S. A. A. Moosavian Jia Jie Zhu Andrea Del Prete Ludovic Righetti 134 15 0 10 Jul 2019
Adaptive Pricing in Insurance: Generalized Linear Models and Gaussian Process Regression Approaches Yuqing Zhang N. Walton 28 3 0 02 Jul 2019
Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalization Jwala Dhamala S. Ghimire J. Sapp B. Horácek Linwei Wang MedIm 68 12 0 01 Jul 2019
Learning to Generate Synthetic 3D Training Data through Hybrid Gradient Dawei Yang Jia Deng 3DH 62 5 0 29 Jun 2019
Multi-objective multi-generation Gaussian process optimizer for design optimization Xiaobiao Huang Minghao Song Zhe Zhang 23 15 0 29 Jun 2019
Bayesian Optimization with Directionally Constrained Search Yongqian Li Yaqiang Yao 17 3 0 22 Jun 2019
Leveraging Reinforcement Learning Techniques for Effective Policy Adoption and Validation Nikki Lijing Kuang C. Leung OffRL 18 2 0 21 Jun 2019
Bayesian Optimisation over Multiple Continuous and Categorical Inputs Binxin Ru A. Alvi Vu Nguyen Michael A. Osborne Stephen J. Roberts 128 97 0 20 Jun 2019
Global optimization via inverse distance weighting and radial basis functions Alberto Bemporad 70 63 0 15 Jun 2019
Region of Attraction for Power Systems using Gaussian Process and Converse Lyapunov Function -- Part I: Theoretical Framework and Off-line Study Chao Zhai H. Nguyen 31 10 0 09 Jun 2019
Bayesian Optimization of Composite Functions Raul Astudillo P. Frazier LLMAG 81 78 0 04 Jun 2019
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning Diego Granziol Binxin Ru S. Zohren Xiaowen Dong Michael A. Osborne Stephen J. Roberts 55 20 0 03 Jun 2019
Characterizing Bias in Classifiers using Generative Models Daniel J. McDuff Shuang Ma Yale Song Ashish Kapoor 92 47 0 30 May 2019
Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees Maria-Florina Balcan Tuomas Sandholm Ellen Vitercik 70 16 0 26 May 2019
Bayesian Optimization with Approximate Set Kernels Jungtaek Kim M. McCourt Tackgeun You Saehoon Kim Seungjin Choi 80 8 0 23 May 2019
Practical Bayesian Optimization with Threshold-Guided Marginal Likelihood Maximization Jungtaek Kim Seungjin Choi 18 0 0 18 May 2019
Reinforcement Learning for Robotics and Control with Active Uncertainty Reduction Narendra Patwardhan Zequn Wang 24 1 0 15 May 2019
Automatic Model Selection for Neural Networks David Laredo Yulin Qin O. Schütze Jianqiao Sun BDL 54 16 0 15 May 2019
Knowing The What But Not The Where in Bayesian Optimization Vu Nguyen Michael A. Osborne 108 38 0 07 May 2019
Bayesian Optimization for Multi-objective Optimization and Multi-point Search Takashige Wada H. Hino 75 20 0 07 May 2019
Lynceus: Cost-efficient Tuning and Provisioning of Data Analytic Jobs Maria Casimiro Diego Didona Paolo Romano L. Rodrigues Willy Zwanepoel David Garlan 48 21 0 06 May 2019
Interpretability with Accurate Small Models Abhishek Ghose Balaraman Ravindran 124 1 0 04 May 2019
Parallel Gaussian process surrogate Bayesian inference with noisy likelihood evaluations Marko Jarvenpaa Michael U. Gutmann Aki Vehtari Pekka Marttinen 118 41 0 03 May 2019