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Jonathan Scarlett

Assistant Professor

Department of Computer Science & Department of Mathematics, National University of Singapore

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I am an assistant professor in the Department of Computer Science and Department of Mathematics at the National University of Singapore, and an affiliate with the Institute of Data Science. I am also a recipient of the National Research Foundation (NRF) Fellowship.

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Tight Regret Bounds for Noisy Optimization of a Brownian Motion

Wang Zexin,Tan Vincent Y. F.,Scarlett Jonathan

Bibtex

Sample Complexity Lower Bounds for Compressive Sensing with Generative Models

Zhaoqiang Liu,Jonathan Scarlett

SPCOM, pp.1-5, (2020)

EIBibtex

Support Recovery in the Phase Retrieval Model: Information-Theoretic Fundamental Limit

Lan V. Truong,Jonathan Scarlett

IEEE Trans. Inf. Theory, no. 12 (2020): 7887-7910

EIBibtex

On Gap-Based Lower Bounding Techniques for Best-Arm Identification

Lan V Truong,Jonathan Scarlett

ENTROPY, no. 7 (2020): 788

WOSEIBibtex

Noisy Non-Adaptive Group Testing: A (Near-)Definite Defectives Approach

Jonathan Scarlett,Oliver Johnson

IEEE Transactions on Information Theory, no. 6 (2020): 3775-3797

EIWOSBibtex

A MaxSAT based Framework for Group Testing

Lorenzo Ciampiconi, Bishwamittra Ghosh,Jonathan Scarlett, Kuldeep S Meel

AAAI Conference on Artificial Intelligence, (2020)

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Improved Bounds and Algorithms for Sparsity Constrained Group Testing

Nelvin Tan,Jonathan Scarlett

arXiv preprint arXiv:2004.03119, (2020)

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On the All Or Nothing Behavior of Bernoulli Group Testing

Lan V Truong, Matthew Aldridge,Jonathan Scarlett

arXiv preprint arXiv:2001.10137, (2020)

Cited by2Bibtex

On Gap Based Lower Bounding Techniques for Best Arm Identification

Lan V Truong,Jonathan Scarlett

Entropy, no. 7 (2020): 788

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On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization

Xu Cai,Jonathan Scarlett

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Information-Theoretic Lower Bounds for Compressive Sensing with Generative Models

Liu Zhaoqiang,Scarlett Jonathan

IEEE J. Sel. Areas Inf. Theory, no. 1 (2020): 292-303

EIBibtex

Stochastic Linear Bandits Robust to Adversarial Attacks

Ilija Bogunovic, Arpan Losalka,Andreas Krause,Jonathan Scarlett

Cited by1Bibtex

The Generalized Lasso with Nonlinear Observations and Generative Priors

Zhaoqiang Liu,Jonathan Scarlett

NIPS 2020, (2020)

EIBibtex

A Fast Binary Splitting Approach to Non-Adaptive Group Testing

Eric Price,Jonathan Scarlett

APPROX/RANDOM, (2020)

EIBibtex

Near-Optimal Sparse Adaptive Group Testing

Tan Nelvin,Scarlett Jonathan

ISIT, pp.1420-1425, (2020)

EIBibtex

Information-Theoretic Foundations of Mismatched Decoding

Scarlett Jonathan,Fàbregas Albert Guillén i, Somekh-Baruch Anelia, Martinez Alfonso

FOUNDATIONS AND TRENDS IN COMMUNICATIONS AND INFORMATION THEORY, no. 2-3 (2020): 149.0-400

Cited by1EIBibtex

Corruption-Tolerant Gaussian Process Bandit Optimization

Bogunovic Ilija,Krause Andreas,Scarlett Jonathan

AISTATS, pp.1071-1081, (2020)

Cited by4EIBibtex

Learning Gaussian Graphical Models via Multiplicative Weights

Chaturvedi Anamay,Scarlett Jonathan

AISTATS, pp.1104-1114, (2020)

EIBibtex

Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors

Liu Zhaoqiang, Gomes Selwyn, Tiwari Avtansh,Scarlett Jonathan

ICML, pp.6216-6225, (2020)

Cited by2EIBibtex

Non-Adaptive Group Testing in the Linear Regime: Strong Converse and Approximate Recovery

Heng Bay Wei,Scarlett Jonathan

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