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"

29 / 279 papers shown

Title
Predictive Entropy Search for Bayesian Optimization with Unknown Constraints José Miguel Hernández-Lobato M. Gelbart Matthew W. Hoffman Ryan P. Adams Zoubin Ghahramani 31 152 0 18 Feb 2015
Gaussian Processes for Data-Efficient Learning in Robotics and Control M. Deisenroth Dieter Fox C. Rasmussen 32 683 0 10 Feb 2015
Distributed Gaussian Processes M. Deisenroth Jun Wei Ng GP 31 340 0 10 Feb 2015
Hyper-parameter optimization of Deep Convolutional Networks for object recognition S. Talathi 37 25 0 30 Jan 2015
Hierarchical Mixture-of-Experts Model for Large-Scale Gaussian Process Regression Jun Wei Ng M. Deisenroth 39 51 0 09 Dec 2014
Automated Machine Learning on Big Data using Stochastic Algorithm Tuning T. Nickson Michael A. Osborne S. Reece Stephen J. Roberts 29 25 0 30 Jul 2014
Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process Hyper-Parameters Ziyun Wang Nando de Freitas 49 89 0 30 Jun 2014
Freeze-Thaw Bayesian Optimization Kevin Swersky Jasper Snoek Ryan P. Adams 59 267 0 16 Jun 2014
Bayesian Optimization with Unknown Constraints M. Gelbart Jasper Snoek Ryan P. Adams 41 442 0 22 Mar 2014
Bayesian Multi-Scale Optimistic Optimization Ziyun Wang B. Shakibi L. Jin Nando de Freitas 80 95 0 27 Feb 2014
Student-t Processes as Alternatives to Gaussian Processes Amar Shah A. Wilson Zoubin Ghahramani GP 47 202 0 18 Feb 2014
GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation Edward Meeds Max Welling 57 123 0 13 Jan 2014
Particle filter-based Gaussian process optimisation for parameter inference J. Dahlin Fredrik Lindsten GP 28 20 0 04 Nov 2013
Active Learning of Linear Embeddings for Gaussian Processes Roman Garnett Michael A. Osborne Philipp Hennig GP 54 91 0 24 Oct 2013
Bayesian Optimization in a Billion Dimensions via Random Embeddings Ziyun Wang Frank Hutter M. Zoghi David Matheson Nando de Freitas 57 436 0 09 Jan 2013
Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms C. Thornton Frank Hutter Holger H. Hoos Kevin Leyton-Brown 35 76 0 18 Aug 2012
Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations Nando de Freitas Alex Smola M. Zoghi 39 110 0 27 Jun 2012
Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization Thomas Desautels Andreas Krause J. W. Burdick 54 471 0 27 Jun 2012
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 29 12,345 0 24 Jun 2012
Active Learning for Matching Problems Laurent Charlin R. Zemel Craig Boutilier 41 10 0 18 Jun 2012
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 140 7,858 0 13 Jun 2012
Decentralized, Adaptive, Look-Ahead Particle Filtering Mohamed Osama Ahmed Pouyan T. Bibalan Nando de Freitas Simon Fauvel 36 3 0 12 Mar 2012
Regret Bounds for Deterministic Gaussian Process Bandits Nando de Freitas Alex Smola M. Zoghi GP 225 10 0 09 Mar 2012
Hybrid Batch Bayesian Optimization J. Azimi A. Jalali Xiaoli Z. Fern 24 70 0 25 Feb 2012
Self-Avoiding Random Dynamics on Integer Complex Systems F. Hamze Ziyun Wang Nando de Freitas 45 25 0 23 Nov 2011
Dynamic Batch Bayesian Optimization J. Azimi A. Jalali Xiaoli Z. Fern 35 7 0 14 Oct 2011
Portfolio Allocation for Bayesian Optimization E. Brochu Matthew W. Hoffman Nando de Freitas 51 278 0 28 Sep 2010
Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization Daniel Golovin Andreas Krause 64 600 0 21 Mar 2010
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design Niranjan Srinivas Andreas Krause Sham Kakade Matthias Seeger 54 1,613 0 21 Dec 2009