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Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian
  Regret Bounds

Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds

3 February 2023
Shion Takeno
Yu Inatsu
Masayuki Karasuyama
ArXivPDFHTML

Papers citing "Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds"

13 / 13 papers shown
Title
Risk-aware black-box portfolio construction using Bayesian optimization with adaptive weighted Lagrangian estimator
Risk-aware black-box portfolio construction using Bayesian optimization with adaptive weighted Lagrangian estimator
Zinuo You
John Cartlidge
Karen Elliott
Menghan Ge
Daniel Gold
27
0
0
18 Apr 2025
Real-Time Roadway Obstacle Detection for Electric Scooters Using Deep Learning and Multi-Sensor Fusion
Real-Time Roadway Obstacle Detection for Electric Scooters Using Deep Learning and Multi-Sensor Fusion
Zeyang Zheng
Arman Hosseini
Dong Chen
Omid Shoghli
Arsalan Heydarian
29
0
0
04 Apr 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
38
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
68
1
0
10 Feb 2025
Regret Analysis for Randomized Gaussian Process Upper Confidence Bound
Regret Analysis for Randomized Gaussian Process Upper Confidence Bound
Shion Takeno
Yu Inatsu
Masayuki Karasuyama
21
0
0
02 Sep 2024
Active Learning for Level Set Estimation Using Randomized Straddle
  Algorithms
Active Learning for Level Set Estimation Using Randomized Straddle Algorithms
Yu Inatsu
Shion Takeno
Kentaro Kutsukake
Ichiro Takeuchi
21
3
0
06 Aug 2024
Optimal Policy Learning with Observational Data in Multi-Action
  Scenarios: Estimation, Risk Preference, and Potential Failures
Optimal Policy Learning with Observational Data in Multi-Action Scenarios: Estimation, Risk Preference, and Potential Failures
Giovanni Cerulli
OffRL
18
0
0
29 Mar 2024
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian
  Regret Bounds
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds
Shion Takeno
Yu Inatsu
Masayuki Karasuyama
Ichiro Takeuchi
15
6
0
07 Nov 2023
Looping in the Human Collaborative and Explainable Bayesian Optimization
Looping in the Human Collaborative and Explainable Bayesian Optimization
Masaki Adachi
Brady Planden
David A. Howey
Michael A. Osborne
Sebastian Orbell
Natalia Ares
Krikamol Maundet
Siu Lun Chau
13
14
0
26 Oct 2023
Self-Correcting Bayesian Optimization through Bayesian Active Learning
Self-Correcting Bayesian Optimization through Bayesian Active Learning
Carl Hvarfner
E. Hellsten
Frank Hutter
Luigi Nardi
GP
19
14
0
21 Apr 2023
Towards Practical Preferential Bayesian Optimization with Skew Gaussian
  Processes
Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes
Shion Takeno
Masahiro Nomura
Masayuki Karasuyama
14
17
0
03 Feb 2023
Bounding Box-based Multi-objective Bayesian Optimization of Risk
  Measures under Input Uncertainty
Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty
Yu Inatsu
Shion Takeno
Hiroyuki Hanada
Kazuki Iwata
Ichiro Takeuchi
11
4
0
27 Jan 2023
Max-value Entropy Search for Efficient Bayesian Optimization
Max-value Entropy Search for Efficient Bayesian Optimization
Zi Wang
Stefanie Jegelka
110
357
0
06 Mar 2017
1