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Jonathan Scarlett — most-cited papers & profile · Reinforcement Learning
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Jonathan Scarlett
15
papers ·
0
citations ·
23
h-index
Data Storage Institute · National University of Singapore
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Most-cited papers
Batched Kernelized Bandits: Refinements and Extensions
2026
Improved Regret Bounds for Linear Bandits with Heavy-Tailed Rewards
2025
Time-Varying Gaussian Process Bandit Optimization
2016
Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization
2017
Tight Regret Bounds for Bayesian Optimization in One Dimension
2018
Corruption-Tolerant Gaussian Process Bandit Optimization
2020
Stochastic Linear Bandits Robust to Adversarial Attacks
2020
Lenient Regret and Good-Action Identification in Gaussian Process Bandits
2021
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits
2022
Max-Quantile Grouped Infinite-Arm Bandits
2022
Regret Bounds for Noise-Free Cascaded Kernelized Bandits
2022
Communication-Constrained Bandits under Additive Gaussian Noise
2023
Complexity of Round-Robin Allocation with Potentially Noisy Queries
2024
No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints
2024
Top co-authors
Ilija Bogunovic
· 4
Andreas Krause
· 3
Zihan Li
· 3
Arpan Losalka
· 2
Volkan Cevher
· 2
and Vincent Y.F. Tan
· 1
Artin Tajdini
· 1
Chenkai Ma
· 1
Ilijia Bogunovic
· 1
Ivan Lau
· 1
Keqin Chen
· 1
Kevin Jamieson
· 1
Topics
stat.ML
cs.LG
cs.IT
math.IT
math.ST
stat.TH
cs.DS
math.PR
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