← Authors

Jonathan Scarlett

39 papers · 2015–2025 · 9 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (10) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (15) 🌈 Renaissance Researcher (6) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (12) 🀝 Dynamic Duo (10) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ”¬ Deep Specialist (11) πŸ’Ž Century Club (39) ⚑ Prolific Year (6) πŸ—ƒοΈ Keyword Collector (136) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (11)

Conferences

AISTATS (11) NIPS (9) ICML (8) AAAI (4) ALT (2) COLT (2) CVPR (1) ICLR (1) UAI (1)

Top co-authors

Volkan Cevher (10) Ilija Bogunovic (9) Zhaoqiang Liu (5) Xu Cai (4) Andreas Krause (4) Zihan Li (3) Arpan Losalka (3) Ivan Lau (2) Subhroshekhar Ghosh (2) Selwyn Gomes (2)

Keywords

gaussian process (14) regret bound (12) bayesian optimization (12) multi-armed bandit (5) sample complexity (5) kernel methods (5) robust optimization (4) group testing (4) reproducing kernel hilbert space (4) bandit optimization (4) compressed sensing (4) black-box optimization (3) generative prior (3) compressive sensing (2) sparse recovery (2) combinatorial optimization (2) upper confidence bound (2) graphical model selection (2) adversarial attack (2) gibbs sampling (2)

Papers

Lower Bounds for Time-Varying Kernelized Bandits AISTATS 2025
Quantile Multi-Armed Bandits with 1-bit Feedback ALT 2025
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization NIPS 2024
Kernelized Normalizing Constant Estimation: Bridging Bayesian Quadrature and Bayesian Optimization AAAI 2024
No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints AISTATS 2024
Max-Quantile Grouped Infinite-Arm Bandits ALT 2023
A Unified Framework for Uniform Signal Recovery in Nonlinear Generative Compressed Sensing NIPS 2023
Communication-Constrained Bandits under Additive Gaussian Noise ICML 2023
Benefits of monotonicity in safe exploration with Gaussian processes UAI 2023
Adversarial Attacks on Gaussian Process Bandits ICML 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning ICML 2022
Max-Min Grouped Bandits AAAI 2022
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits NIPS 2022
Generative Principal Component Analysis ICLR 2022
Gaussian Process Bandit Optimization with Few Batches AISTATS 2022
Stochastic Linear Bandits Robust to Adversarial Attacks AISTATS 2021
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors NIPS 2021
High-Dimensional Bayesian Optimization via Tree-Structured Additive Models AAAI 2021
On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization ICML 2021
Lenient Regret and Good-Action Identification in Gaussian Process Bandits ICML 2021
Open Problem: Tight Online Confidence Intervals for RKHS Elements COLT 2021
Learning Gaussian Graphical Models via Multiplicative Weights AISTATS 2020
The Generalized Lasso with Nonlinear Observations and Generative Priors NIPS 2020
A MaxSAT-Based Framework for Group Testing AAAI 2020
Corruption-Tolerant Gaussian Process Bandit Optimization AISTATS 2020
A Characteristic Function Approach to Deep Implicit Generative Modeling CVPR 2020
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors ICML 2020
Learning Erdos-Renyi Random Graphs via Edge Detecting Queries NIPS 2019
Tight Regret Bounds for Bayesian Optimization in One Dimension ICML 2018
Adversarially Robust Optimization with Gaussian Processes NIPS 2018
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups AISTATS 2018
Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization COLT 2017
Lower Bounds on Active Learning for Graphical Model Selection AISTATS 2017
Robust Submodular Maximization: A Non-Uniform Partitioning Approach ICML 2017
Phase Transitions in the Pooled Data Problem NIPS 2017
Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices AISTATS 2016
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation NIPS 2016
Time-Varying Gaussian Process Bandit Optimization AISTATS 2016
Sparsistency of \ell_1-Regularized M-Estimators AISTATS 2015