133 citations · 803 across the 68 of their papers we have counts for
8 papers · 1 filter
Adversarially Robust Optimization with Gaussian Processes
Ilija Bogunovic, Jonathan Scarlett, Stefanie Jegelka +1
In this paper, we consider the problem of Gaussian process (GP) optimization with an added robustness requirement: The returned point may be perturbed by an adversary, and we requi…
Noisy Non-Adaptive Group Testing: A (Near-)Definite Defectives Approach
Jonathan Scarlett, Oliver Johnson
The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of possibly-noisy tests, and is relevant in applicatio…
Cross-Sender Bit-Mixing Coding
Steffen Bondorf, Binbin Chen, Jonathan Scarlett +2
Scheduling to avoid packet collisions is a long-standing challenge in networking, and has become even trickier in wireless networks with multiple senders and multiple receivers. In…
Learning-Based Compressive MRI
Baran Gözcü, Rabeeh Karimi Mahabadi, Yen-Huan Li +4
In the area of magnetic resonance imaging (MRI), an extensive range of non-linear reconstruction algorithms have been proposed that can be used with general Fourier subsampling pat…
Tight Regret Bounds for Bayesian Optimization in One Dimension
Jonathan Scarlett
We consider the problem of Bayesian optimization (BO) in one dimension, under a Gaussian process prior and Gaussian sampling noise. We provide a theoretical analysis showing that,…
Generalized Random Gilbert-Varshamov Codes
Anelia Somekh-Baruch, Jonathan Scarlett, Albert Guillén i Fàbregas
We introduce a random coding technique for transmission over discrete memoryless channels, reminiscent of the basic construction attaining the Gilbert-Varshamov bound for codes in…
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups
Paul Rolland, Jonathan Scarlett, Ilija Bogunovic +1
Bayesian optimization (BO) is a popular technique for sequential black-box function optimization, with applications including parameter tuning, robotics, environmental monitoring,…
Noisy Adaptive Group Testing: Bounds and Algorithms
Jonathan Scarlett
The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of possibly-noisy tests, and is relevant in applicatio…