Jonathan Scarlett
41 papers · 2015–2026 · 9 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 13 separate collaboration groups - the largest holds only 41% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Jonathan Scarlett?
5 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Volkan Cevher, Ilija Bogunovic, Andreas Krause
17 papers
· 2015–2024
· AISTATS, NeurIPS, UAI
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No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints
AISTATS 2024
Benefits of monotonicity in safe exploration with Gaussian processes
UAI 2023
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits
NeurIPS 2022
Gaussian Process Bandit Optimization with Few Batches
AISTATS 2022
Stochastic Linear Bandits Robust to Adversarial Attacks
AISTATS 2021
Corruption-Tolerant Gaussian Process Bandit Optimization
AISTATS 2020
Learning Erdos-Renyi Random Graphs via Edge Detecting Queries
NeurIPS 2019
Adversarially Robust Optimization with Gaussian Processes
NeurIPS 2018
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups
AISTATS 2018
Lower Bounds on Active Learning for Graphical Model Selection
AISTATS 2017
Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization
COLT 2017
Phase Transitions in the Pooled Data Problem
NeurIPS 2017
Robust Submodular Maximization: A Non-Uniform Partitioning Approach
ICML 2017
Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices
AISTATS 2016
Time-Varying Gaussian Process Bandit Optimization
AISTATS 2016
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation
NeurIPS 2016
Sparsistency of \ell_1-Regularized M-Estimators
AISTATS 2015
8 papers whose co-authors appear nowhere else under this name
A Distribution Testing Approach to Clustering Distributions
COLT 2026
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization
NeurIPS 2024
Communication-Constrained Bandits under Additive Gaussian Noise
ICML 2023
Max-Min Grouped Bandits
AAAI 2022
A Characteristic Function Approach to Deep Implicit Generative Modeling
CVPR 2020
A MaxSAT-Based Framework for Group Testing
AAAI 2020
Learning Gaussian Graphical Models via Multiplicative Weights
AISTATS 2020
Tight Regret Bounds for Bayesian Optimization in One Dimension
ICML 2018