Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

21 December 2009

Papers citing "Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design"

50 / 617 papers shown

Title
Gamifying optimization: a Wasserstein distance-based analysis of human search Antonio Candelieri Andrea Ponti Francesco Archetti 23 0 0 12 Dec 2021
Structure-Preserving Learning Using Gaussian Processes and Variational Integrators Jan Brüdigam Martin Schuck A. Capone Stefan Sosnowski Sandra Hirche 19 4 0 10 Dec 2021
Indexed Minimum Empirical Divergence for Unimodal Bandits Hassan Saber Pierre Ménard Odalric-Ambrym Maillard 17 3 0 02 Dec 2021
Contextual Combinatorial Multi-output GP Bandits with Group Constraints Sepehr Elahi Baran Atalar Sevda Öğüt Cem Tekin 30 2 0 29 Nov 2021
Towards Autonomous Driving of Personal Mobility with Small and Noisy Dataset using Tsallis-statistics-based Behavioral Cloning Taisuke Kobayashi Takahito Enomoto 29 3 0 29 Nov 2021
Transfer Learning with Gaussian Processes for Bayesian Optimization Petru Tighineanu Kathrin Skubch P. Baireuther Attila Reiss Felix Berkenkamp Julia Vinogradska 22 32 0 22 Nov 2021
Gaussian Process Inference Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits Hao Chen Lili Zheng Raed Al Kontar Garvesh Raskutti 31 3 0 19 Nov 2021
Bayesian Optimization for Cascade-type Multi-stage Processes Shunya Kusakawa Shion Takeno Yu Inatsu Kentaro Kutsukake S. Iwazaki Takashi Nakano T. Ujihara Masayuki Karasuyama Ichiro Takeuchi 25 18 0 16 Nov 2021
Stochastic Gradient Line Bayesian Optimization for Efficient Noise-Robust Optimization of Parameterized Quantum Circuits Shiro Tamiya H. Yamasaki 26 24 0 15 Nov 2021
Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes Panagiotis Petsagkourakis Benoît Chachuat Ehecatl Antonio del Rio Chanona 27 7 0 10 Nov 2021
Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers Julian Katz-Samuels Blake Mason Kevin G. Jamieson R. Nowak 11 0 0 09 Nov 2021
Risk-averse Heteroscedastic Bayesian Optimization A. Makarova Ilnura N. Usmanova Ilija Bogunovic Andreas Krause 35 35 0 05 Nov 2021
Adaptive Low-Pass Filtering using Sliding Window Gaussian Processes Alejandro Jose Ordóñez Conejo Armin Lederer Sandra Hirche 15 4 0 05 Nov 2021
Contextual Bayesian optimization with binary outputs T. Fauvel M. Chalk 40 3 0 05 Nov 2021
Overcoming Digital Gravity when using AI in Public Health Decisions S. Remy Aisha Walcott-Bryant Nelson Bore C. Wachira J. Kuehnert AI4CE 8 1 0 05 Nov 2021
DOCKSTRING: easy molecular docking yields better benchmarks for ligand design Miguel García-Ortegón G. Simm Austin Tripp José Miguel Hernández-Lobato A. Bender S. Bacallado 42 75 0 29 Oct 2021
Differentially Private Federated Bayesian Optimization with Distributed Exploration Zhongxiang Dai K. H. Low Patrick Jaillet FedML 26 41 0 27 Oct 2021
Bayesian Optimization and Deep Learning forsteering wheel angle prediction Alessandro Riboni Nicolò Ghioldi Antonio Candelieri M. Borrotti LLMSV 27 10 0 22 Oct 2021
Sensing Cox Processes via Posterior Sampling and Positive Bases Mojmír Mutný Andreas Krause 13 5 0 21 Oct 2021
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game Shuang Qiu Jieping Ye Zhaoran Wang Zhuoran Yang OffRL 47 23 0 19 Oct 2021
Set-based State Estimation with Probabilistic Consistency Guarantee under Epistemic Uncertainty Shen Li Theodoros Stouraitis Michael Gienger S. Vijayakumar J. Shah 14 8 0 18 Oct 2021
An active learning approach for improving the performance of equilibrium based chemical simulations M. Savino Céline Lévy-Leduc M. Leconte B. Cochepin 20 5 0 15 Oct 2021
Gaussian Process Bandit Optimization with Few Batches Zihan Li Jonathan Scarlett GP 135 47 0 15 Oct 2021
Contextual Combinatorial Bandits with Changing Action Sets via Gaussian Processes Andi Nika Sepehr Elahi Cem Tekin 30 2 0 05 Oct 2021
$Δ$ -UQ: Accurate Uncertainty Quantification via Anchor Marginalization Rushil Anirudh Jayaraman J. Thiagarajan 38 1 0 05 Oct 2021
Machine Learning with Knowledge Constraints for Process Optimization of Open-Air Perovskite Solar Cell Manufacturing Zhe Liu Nicholas Rolston Austin C. Flick T. Colburn Zekun Ren R. Dauskardt Tonio Buonassisi 35 116 0 01 Oct 2021
Genealogical Population-Based Training for Hyperparameter Optimization Antoine Scardigli P. Fournier Matteo Vilucchio D. Naccache GP 22 0 0 30 Sep 2021
Pre-trained Gaussian processes for Bayesian optimization Zehao Wang George E. Dahl Kevin Swersky Chansoo Lee Zachary Nado Justin Gilmer Jasper Snoek Zoubin Ghahramani 70 40 0 16 Sep 2021
Batched Data-Driven Evolutionary Multi-Objective Optimization Based on Manifold Interpolation Ke Li Renzhi Chen 32 27 0 12 Sep 2021
Active Multi-Object Exploration and Recognition via Tactile Whiskers Chenxi Xiao Shujia Xu Wenzhuo Wu J. Wachs 36 12 0 08 Sep 2021
Safety-Critical Learning of Robot Control with Temporal Logic Specifications Mingyu Cai C. Vasile 40 4 0 07 Sep 2021
Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications A. Capone Armin Lederer Sandra Hirche 32 18 0 06 Sep 2021
Select Wisely and Explain: Active Learning and Probabilistic Local Post-hoc Explainability Aditya Saini Ranjitha Prasad BDL 11 13 0 16 Aug 2021
Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputers Anh Tran 32 0 0 12 Aug 2021
Model-Based Opponent Modeling Xiaopeng Yu Jiechuan Jiang Wanpeng Zhang Haobin Jiang Zongqing Lu OffRL 41 28 0 04 Aug 2021
Active Learning in Gaussian Process State Space Model H. Yu Dingling Yao Christoph Zimmer Marc Toussaint D. Nguyen-Tuong GP 22 4 0 30 Jul 2021
Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization Q. Nguyen Zhaoxuan Wu K. H. Low Patrick Jaillet 49 12 0 30 Jul 2021
Physics-constrained Deep Learning for Robust Inverse ECG Modeling Jianxin Xie B. Yao 30 22 0 26 Jul 2021
High-Dimensional Simulation Optimization via Brownian Fields and Sparse Grids Liang Ding Rui Tuo Xiaowei Zhang 27 3 0 19 Jul 2021
Contextual Games: Multi-Agent Learning with Side Information Pier Giuseppe Sessa Ilija Bogunovic Andreas Krause Maryam Kamgarpour 54 21 0 13 Jul 2021
Efficient and Reactive Planning for High Speed Robot Air Hockey Puze Liu Davide Tateo Haitham Bou-Ammar Jan Peters 41 18 0 13 Jul 2021
Scaling Gaussian Processes with Derivative Information Using Variational Inference Misha Padidar Xinran Zhu Leo Huang Jacob R. Gardner D. Bindel BDL 19 18 0 08 Jul 2021
Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modeling Kai Wang Bryan Wilder S. Suen B. Dilkina Milind Tambe 195 0 0 07 Jul 2021
A Short Note on the Relationship of Information Gain and Eluder Dimension Kaixuan Huang Sham Kakade Jason D. Lee Qi Lei 8 8 0 06 Jul 2021
Weighted Gaussian Process Bandits for Non-stationary Environments Yuntian Deng Xingyu Zhou Baekjin Kim Ambuj Tewari Abhishek Gupta Ness B. Shroff 19 23 0 06 Jul 2021
A Map of Bandits for E-commerce Yi Liu Lihong Li 16 10 0 01 Jul 2021
Counterfactual Explanations for Arbitrary Regression Models Thomas Spooner Danial Dervovic Jason Long Jon Shepard Jiahao Chen Daniele Magazzeni 24 26 0 29 Jun 2021
An Efficient Batch Constrained Bayesian Optimization Approach for Analog Circuit Synthesis via Multi-objective Acquisition Ensemble Shuhan Zhang Fan Yang Changhao Yan Dian Zhou Xuan Zeng 31 65 0 28 Jun 2021
Machine Learning based optimization for interval uncertainty propagation Alice Cicirello Filippo Giunta 18 10 0 21 Jun 2021
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks Shibo Li Robert M. Kirby Shandian Zhe 35 13 0 18 Jun 2021