Selected Publications by Topic


For a more complete list, see my Google Scholar profile or my CV

Survey/Tutorial

Group Testing: An Information Theory Perspective
Matthew Aldridge, Oliver Johnson, and Jonathan Scarlett
Submitted to Foundations and Trends in Communications and Information Theory (Preprint)
[arxiv]
An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation
Jonathan Scarlett and Volkan Cevher
Book chapter in Information-Theoretic Methods in Data Science (expected for 2019 publication)
[arxiv]

Optimization in Machine Learning

Adversarially Robust Optimization with Gaussian Processes
Ilija Bogunovic, Jonathan Scarlett, Stefanie Jegelka, and Volkan Cevher
Conference on Neural Information Processing Systems (NeurIPS), 2018
[nips] [arxiv]
Tight Regret Bounds for Bayesian Optimization in One Dimension
Jonathan Scarlett
International Conference on Machine Learning (ICML), 2018
[pmlr] [arxiv]
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups
Paul Rolland, Jonathan Scarlett, Ilija Bogunovic, and Volkan Cevher
International Conference on Artificial Intelligence and Statistics (AISTATS), 2018
[pmlr] [arxiv]
Robust Submodular Maximization: A Non-Uniform Partitioning Approach
Ilija Bogunovic, Slobodan Mitrovic, Jonathan Scarlett, and Volkan Cevher
International Conference on Machine Learning (ICML), 2017
[pmlr] [arxiv]
Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization
Jonathan Scarlett, Ilija Bogunovic, and Volkan Cevher
Conference on Learning Theory (COLT), 2017
[pmlr] [arxiv]
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation
Ilija Bogunovic, Jonathan Scarlett, Andreas Krause, and Volkan Cevher
Conference on Neural Information Processing Systems (NIPS), 2016
[nips] [arxiv]
Time-Varying Gaussian Process Bandit Optimization
Ilija Bogunovic, Jonathan Scarlett, and Volkan Cevher
International Conference on Artificial Intelligence and Statistics (AISTATS), 2016
[pmlr] [arxiv]

Group Testing and Pooled Data

Noisy Non-Adaptive Group Testing: A (Near-)Definite Defectives Approach
Jonathan Scarlett and Oliver Johnson
Submitted to IEEE Transactions on Information Theory, 2018 (Preprint)
[arxiv]
Noisy Adaptive Group Testing: Bounds and Algorithms
Jonathan Scarlett
IEEE Transactions on Information Theory, Volume 65, Issue 6, pp. 3646-3661, June 2019.
[ieee][arxiv]
Performance of Group Testing Algorithms with Near-Constant Tests-Per-Item
Oliver Johnson, Matthew Aldridge, and Jonathan Scarlett
IEEE Transactions on Information Theory, Volume 65, Issue 2, pp. 707-723, Feb. 2019
[ieee] [arxiv]
Near-Optimal Noisy Group Testing via Separate Decoding of Items
Jonathan Scarlett and Volkan Cevher
IEEE Journal on Selected Topics in Signal Processing (Special Issue on Information-Theoretic Methods in Data Acquisition, Analysis, and Processing), Volume 12, Issue 5, pp. 902-915, Oct. 2018
[ieee] [arxiv]
Phase Transitions in the Pooled Data Problem
Jonathan Scarlett and Volkan Cevher
Conference on Neural Information Processing Systems (NIPS), 2017
[nips] [arxiv]
Phase Transitions in Group Testing
Jonathan Scarlett and Volkan Cevher
ACM-SIAM Symposium on Discrete Algorithms (SODA), 2016
[acm] [epfl]

Graphical Models

Learning Erdős-Rényi Random Graphs via Edge Detecting Queries
Zihan Li, Matthias Fresacher, and Jonathan Scarlett
Submitted for publication (Preprint)
[arxiv]
Lower Bounds on Active Learning for Graphical Model Selection
Jonathan Scarlett and Volkan Cevher
International Conference on Artificial Intelligence and Statistics (AISTATS), 2017
[pmlr] [arxiv]
On the Difficulty of Selecting Ising Models with Approximate Recovery
Jonathan Scarlett and Volkan Cevher
IEEE Transactions on Signal and Information Processing over Networks (Special Issue on Inference and Learning over Networks), Volume 2, Issue 4, pp. 625-638, July 2016
[ieee] [arxiv]
Partial Recovery Bounds for the Sparse Stochastic Block Model
Jonathan Scarlett and Volkan Cevher
IEEE International Symposium on Information Theory (ISIT), 2016
[ieee] [arxiv]

Sparsity and Compressive Sensing

Support Recovery in the Phase Retrieval Model: Information-Theoretic Fundamental Limits
Lan V. Truong and Jonathan Scarlett
Submitted to IEEE Transactions on Information Theory, 2018 (Preprint)
[arxiv]
An Adaptive Sublinear-Time Block Sparse Fourier Transform
Volkan Cevher, Michael Kapralov, Jonathan Scarlett, and Amir Zandieh
ACM Symposium on Theory of Computing (STOC), 2017
[acm] [arxiv]
Limits on Support Recovery with Probabilistic Models: An Information-Theoretic Framework
Jonathan Scarlett and Volkan Cevher
IEEE Transactions on Information Theory, Volume 63, Issue 1, pp. 593-620, Jan. 2017
[ieee] [arxiv]
Learning-Based Compressive Subsampling
Luca Baldassarre, Yen-Huan Li, Jonathan Scarlett, Baran Gözcü, Ilija Bogunovic, and Volkan Cevher
IEEE Journal on Selected Topics in Signal Processing (Special Issue on Structured Matrices in Signal and Data Processing), Volume 10, Issue 4, pp. 809-822, March 2016
[ieee] [arxiv]
Sparsistency of l1-Regularized M-estimators
Yen-Huan Li, Jonathan Scarlett, Pradeep Ravikumar, and Volkan Cevher
International Conference on Artificial Intelligence and Statistics (AISTATS), 2015
[pmlr] [arxiv]
Compressed Sensing with Prior Information: Information-Theoretic Limits and Practical Decoders
Jonathan Scarlett, Jamie Evans, and Subhrakanti Dey
IEEE Transactions on Signal Processing, Volume 61, Issue 2, pp. 427-439, Jan. 2013
[ieee]

Mismatched Decoding in Information Theory

Mismatched Multi-Letter Successive Decoding for the Multiple-Access Channel
Jonathan Scarlett, Alfonso Martinez, and Albert Guillén i Fàbregas
IEEE Transactions on Information Theory, Volume 64, Issue 4, pp. 2253-2266, April 2018
[ieee] [arxiv]
The Dispersion of Nearest-Neighbor Decoding for Additive Non-Gaussian Channels
Jonathan Scarlett, Vincent Y. F. Tan, and Giuseppe Durisi
IEEE Transactions on Information Theory, Volume 63, Issue 1, pp. 81-92, Jan. 2017
[ieee] [arxiv]
Multiuser Random Coding Techniques for Mismatched Decoding
Jonathan Scarlett, Alfonso Martinez, and Albert Guillén i Fàbregas
IEEE Transactions on Information Theory, Volume 62, Issue 7, pp. 3950-3970, July 2016
[ieee] [arxiv]
A Counter-Example to the Mismatched Decoding Converse for Binary-Input Discrete Memoryless Channels
Jonathan Scarlett, Anelia Somekh-Baruch. Alfonso Martinez, and Albert Guillén i Fàbregas
IEEE Transactions on Information Theory, Volume 61, Issue 10, pp. 5387-5395, Oct. 2015
[ieee] [arxiv]
Mismatched Decoding: Error Exponents, Second-Order Rates and Saddlepoint Approximations
Jonathan Scarlett, Alfonso Martinez, and Albert Guillén i Fàbregas
IEEE Transactions on Information Theory, Volume 60, Issue 5, pp. 2647-2666, May 2014
[ieee] [arxiv]

Refined Asymptotics in Information Theory

Generalized Random Gilbert-Varshamov Codes
Anelia Somekh-Baruch, Jonathan Scarlett, and Albert Guillén i Fàbregas
IEEE Transactions on Information Theory, Volume 65, Issue 6, pp. 3452-3469, June 2019
[ieee] [arxiv]
Second-Order Asymptotics for the Gaussian MAC with Degraded Message Sets
Jonathan Scarlett and Vincent Y. F. Tan
IEEE Transactions on Information Theory, Volume 61, Issue 12, pp. 6700-6718, Dec. 2015
[ieee] [arxiv]
On the Dispersions of the Gel'fand-Pinsker Channel and Dirty Paper Coding
Jonathan Scarlett
IEEE Transactions on Information Theory, Volume 61, Issue 9, pp. 4569-4586, Sept. 2015
[ieee] [arxiv]
Second-Order Rate Region of Constant-Composition Codes for the Multiple-Access Channel
Jonathan Scarlett, Alfonso Martinez, and Albert Guillén i Fàbregas
IEEE Transactions on Information Theory, Volume 61, Issue 1, pp. 157-172, Jan. 2015
[ieee] [arxiv]
Expurgated Random-Coding Ensembles: Exponents, Refinements and Connections
Jonathan Scarlett, Li Peng, Neri Merhav, Alfonso Martinez, and Albert Guillén i Fàbregas
IEEE Transactions on Information Theory, Volume 60, Issue 8, pp. 4449-4462, Aug. 2014
[ieee] [arxiv]