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2108.09262
Cited By
Optimal Order Simple Regret for Gaussian Process Bandits
20 August 2021
Sattar Vakili
N. Bouziani
Sepehr Jalali
A. Bernacchia
Da-shan Shiu
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Papers citing
"Optimal Order Simple Regret for Gaussian Process Bandits"
41 / 41 papers shown
Regret Analysis of Posterior Sampling-Based Expected Improvement for Bayesian Optimization
Shion Takeno
Yu Inatsu
Masayuki Karasuyama
I. Takeuchi
376
3
0
13 Jul 2025
Improved Regret Bounds for Gaussian Process Upper Confidence Bound in Bayesian Optimization
Shogo Iwazaki
GP
346
9
0
02 Jun 2025
Quick-Draw Bandits: Quickly Optimizing in Nonstationary Environments with Extremely Many Arms
Knowledge Discovery and Data Mining (KDD), 2025
Derek Everett
Fred Lu
Edward Raff
Fernando Camacho
James Holt
321
0
0
30 May 2025
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
Aya Kayal
Sattar Vakili
Laura Toni
Da-shan Shiu
A. Bernacchia
206
1
0
29 May 2025
Gaussian Process Upper Confidence Bound Achieves Nearly-Optimal Regret in Noise-Free Gaussian Process Bandits
Shogo Iwazaki
288
1
0
26 Feb 2025
Distributionally Robust Active Learning for Gaussian Process Regression
Shion Takeno
Yoshito Okura
Yu Inatsu
Aoyama Tatsuya
Tomonari Tanaka
...
Noriaki Hashimoto
Taro Murayama
Hanju Lee
Shinya Kojima
Ichiro Takeuchi
OOD
GP
543
0
0
24 Feb 2025
Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance
S. Iwazaki
Shion Takeno
392
9
0
10 Feb 2025
Differentially Private Kernelized Contextual Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Nikola Pavlovic
Sudeep Salgia
Qing Zhao
309
3
0
13 Jan 2025
Distributed Thompson sampling under constrained communication
IEEE Control Systems Letters (L-CSS), 2024
Saba Zerefa
Tongzheng Ren
Haitong Ma
Na Li
395
2
0
03 Jan 2025
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
Neural Information Processing Systems (NeurIPS), 2024
Sattar Vakili
Julia Olkhovskaya
345
3
0
30 Oct 2024
Sample-efficient Bayesian Optimisation Using Known Invariances
Neural Information Processing Systems (NeurIPS), 2024
Theodore Brown
Alexandru Cioba
Ilija Bogunovic
221
5
0
22 Oct 2024
Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning
Sattar Vakili
OffRL
386
2
0
21 Jun 2024
Graph Neural Thompson Sampling
Shuang Wu
Arash A. Amini
411
1
0
15 Jun 2024
Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared Randomness
Nikola Pavlovic
Sudeep Salgia
Qing Zhao
240
0
0
20 Feb 2024
PINN-BO: A Black-box Optimization Algorithm using Physics-Informed Neural Networks
Dat Phan-Trong
Hung The Tran
A. Shilton
Sunil R. Gupta
209
0
0
05 Feb 2024
Kernelized Normalizing Constant Estimation: Bridging Bayesian Quadrature and Bayesian Optimization
AAAI Conference on Artificial Intelligence (AAAI), 2024
Xu Cai
Jonathan Scarlett
221
0
0
11 Jan 2024
Distributed Optimization via Kernelized Multi-armed Bandits
Ayush Rai
Shaoshuai Mou
252
0
0
07 Dec 2023
Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency
International Conference on Machine Learning (ICML), 2023
Sudeep Salgia
Sattar Vakili
Qing Zhao
464
13
0
23 Oct 2023
Pure Exploration in Asynchronous Federated Bandits
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Zichen Wang
Chuanhao Li
Chenyu Song
Lianghui Wang
Quanquan Gu
Huazheng Wang
FedML
321
6
0
17 Oct 2023
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Shyam Sundhar Ramesh
Pier Giuseppe Sessa
Yifan Hu
Andreas Krause
Ilija Bogunovic
OOD
262
23
0
05 Sep 2023
Kernelized Reinforcement Learning with Order Optimal Regret Bounds
Neural Information Processing Systems (NeurIPS), 2023
Sattar Vakili
Julia Olkhovskaya
465
17
0
13 Jun 2023
Training-Free Neural Active Learning with Initialization-Robustness Guarantees
International Conference on Machine Learning (ICML), 2023
Apivich Hemachandra
Zhongxiang Dai
Jasraj Singh
See-Kiong Ng
K. H. Low
AAML
289
8
0
07 Jun 2023
Neural-BO: A Black-box Optimization Algorithm using Deep Neural Networks
Neurocomputing (Neurocomputing), 2023
Dat Phan-Trong
Hung The Tran
Sunil R. Gupta
333
11
0
03 Mar 2023
Sample Complexity of Kernel-Based Q-Learning
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Sing-Yuan Yeh
Fu-Chieh Chang
Chang-Wei Yueh
Pei-Yuan Wu
A. Bernacchia
Sattar Vakili
OffRL
318
7
0
01 Feb 2023
Delayed Feedback in Kernel Bandits
International Conference on Machine Learning (ICML), 2023
Sattar Vakili
Danyal Ahmed
A. Bernacchia
Ciara Pike-Burke
284
8
0
01 Feb 2023
(Private) Kernelized Bandits with Distributed Biased Feedback
Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 2023
Fengjiao Li
Xingyu Zhou
Bo Ji
458
6
0
28 Jan 2023
Benefits of Monotonicity in Safe Exploration with Gaussian Processes
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Arpan Losalka
Jonathan Scarlett
236
1
0
03 Nov 2022
Lower Bounds on the Worst-Case Complexity of Efficient Global Optimization
Wenjie Xu
Yuning Jiang
E. Maddalena
Colin N. Jones
244
9
0
20 Sep 2022
Collaborative Learning in Kernel-based Bandits for Distributed Users
IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022
Sudeep Salgia
Sattar Vakili
Qing Zhao
FedML
289
7
0
16 Jul 2022
Graph Neural Network Bandits
Neural Information Processing Systems (NeurIPS), 2022
Parnian Kassraie
Andreas Krause
Ilija Bogunovic
326
14
0
13 Jul 2022
Provably and Practically Efficient Neural Contextual Bandits
International Conference on Machine Learning (ICML), 2022
Sudeep Salgia
Sattar Vakili
Qing Zhao
288
12
0
31 May 2022
On Average-Case Error Bounds for Kernel-Based Bayesian Quadrature
Xu Cai
Chi Thanh Lam
Jonathan Scarlett
357
4
0
22 Feb 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning
International Conference on Machine Learning (ICML), 2022
Sattar Vakili
Jonathan Scarlett
Da-shan Shiu
A. Bernacchia
390
22
0
08 Feb 2022
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits
Neural Information Processing Systems (NeurIPS), 2022
Ilija Bogunovic
Zihan Li
Andreas Krause
Jonathan Scarlett
325
11
0
03 Feb 2022
Rate-optimal Bayesian Simple Regret in Best Arm Identification
Junpei Komiyama
Kaito Ariu
Masahiro Kato
Chao Qin
581
12
0
18 Nov 2021
Nearly Optimal Algorithms for Level Set Estimation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Blake Mason
Romain Camilleri
Subhojyoti Mukherjee
Kevin Jamieson
Robert D. Nowak
Lalit P. Jain
283
26
0
02 Nov 2021
Collaborative Pure Exploration in Kernel Bandit
International Conference on Learning Representations (ICLR), 2021
Yihan Du
Wei Chen
Yuko Kuroki
Longbo Huang
512
13
0
29 Oct 2021
Open Problem: Tight Online Confidence Intervals for RKHS Elements
Annual Conference Computational Learning Theory (COLT), 2021
Sattar Vakili
John Scarlett
T. Javidi
293
23
0
28 Oct 2021
Gaussian Process Bandit Optimization with Few Batches
Zihan Li
Jonathan Scarlett
GP
559
58
0
15 Oct 2021
Uniform Generalization Bounds for Overparameterized Neural Networks
Sattar Vakili
Michael Bromberg
Jezabel R. Garcia
Da-shan Shiu
A. Bernacchia
421
24
0
13 Sep 2021
Tight Regret Bounds for Bayesian Optimization in One Dimension
Jonathan Scarlett
545
34
0
30 May 2018
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