Jonathan Scarlett

Orcid: 0000-0003-1403-9160

Affiliations:
  • National University of Singapore, Singapore


According to our database1, Jonathan Scarlett authored at least 138 papers between 2011 and 2024.

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Bibliography

2024
Maxflow-Based Bounds for Low-Rate Information Propagation Over Noisy Networks.
IEEE Trans. Inf. Theory, June, 2024

Mismatched Rate-Distortion Theory: Ensembles, Bounds, and General Alphabets.
IEEE Trans. Inf. Theory, 2024

Complexity of Round-Robin Allocation with Potentially Noisy Queries.
CoRR, 2024

Exact Thresholds for Noisy Non-Adaptive Group Testing.
CoRR, 2024

No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Kernelized Normalizing Constant Estimation: Bridging Bayesian Quadrature and Bayesian Optimization.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Multi-Bit Relaying Over a Tandem of Channels.
IEEE Trans. Inf. Theory, June, 2023

Performance Bounds for Group Testing With Doubly-Regular Designs.
IEEE Trans. Inf. Theory, February, 2023

Optimal 1-bit Error Exponent for 2-hop Relaying with Binary-Input Channels.
CoRR, 2023

Approximate Message Passing with Rigorous Guarantees for Pooled Data and Quantitative Group Testing.
CoRR, 2023

Concomitant Group Testing.
CoRR, 2023

Benefits of monotonicity in safe exploration with Gaussian processes.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

A Unified Framework for Uniform Signal Recovery in Nonlinear Generative Compressed Sensing.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Communication-Constrained Bandits under Additive Gaussian Noise.
Proceedings of the International Conference on Machine Learning, 2023

For One and All: Individual and Group Fairness in the Allocation of Indivisible Goods.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Max-Quantile Grouped Infinite-Arm Bandits.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022
Theoretical Perspectives on Deep Learning Methods in Inverse Problems.
IEEE J. Sel. Areas Inf. Theory, September, 2022

Guest Editorial.
IEEE J. Sel. Areas Inf. Theory, September, 2022

Tight Regret Bounds for Noisy Optimization of a Brownian Motion.
IEEE Trans. Signal Process., 2022

Model-Based and Graph-Based Priors for Group Testing.
IEEE Trans. Signal Process., 2022

Noisy Adaptive Group Testing via Noisy Binary Search.
IEEE Trans. Inf. Theory, 2022

Simple Coding Techniques for Many-Hop Relaying.
IEEE Trans. Inf. Theory, 2022

Near-Optimal Sparsity-Constrained Group Testing: Improved Bounds and Algorithms.
IEEE Trans. Inf. Theory, 2022

Regret Bounds for Noise-Free Cascaded Kernelized Bandits.
CoRR, 2022

Order-Optimal Error Bounds for Noisy Kernel-Based Bayesian Quadrature.
CoRR, 2022

A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Simple Coding Scheme Attaining Positive Information Velocity.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Multi-User Random Coding Techniques for Mismatched Rate-Distortion Theory.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Group Testing with Blocks of Positives.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Universal 1-Bit Compressive Sensing for Bounded Dynamic Range Signals.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning.
Proceedings of the International Conference on Machine Learning, 2022

Adversarial Attacks on Gaussian Process Bandits.
Proceedings of the International Conference on Machine Learning, 2022

Generative Principal Component Analysis.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Data-Driven Algorithms for Gaussian Measurement Matrix Design in Compressive Sensing.
Proceedings of the IEEE International Conference on Acoustics, 2022

Gaussian Process Bandit Optimization with Few Batches.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Max-Min Grouped Bandits.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Optimal Rates of Teaching and Learning Under Uncertainty.
IEEE Trans. Inf. Theory, 2021

Sublinear-Time Non-Adaptive Group Testing With O(k log n) Tests via Bit-Mixing Coding.
IEEE Trans. Inf. Theory, 2021

On Architecture Selection for Linear Inverse Problems with Untrained Neural Networks.
Entropy, 2021

Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors.
CoRR, 2021

Fast Splitting Algorithms for Sparsity-Constrained and Noisy Group Testing.
CoRR, 2021

Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors.
Proceedings of the IEEE Information Theory Workshop, 2021

An Analysis of the DD Algorithm for Group Testing with Size-Constrained Tests.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Optimal Rates of Teaching and Learning Under Binary Symmetric Noise.
Proceedings of the IEEE International Symposium on Information Theory, 2021

On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization.
Proceedings of the 38th International Conference on Machine Learning, 2021

Lenient Regret and Good-Action Identification in Gaussian Process Bandits.
Proceedings of the 38th International Conference on Machine Learning, 2021

Open Problem: Tight Online Confidence Intervals for RKHS Elements.
Proceedings of the Conference on Learning Theory, 2021

Stochastic Linear Bandits Robust to Adversarial Attacks.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

High-Dimensional Bayesian Optimization via Tree-Structured Additive Models.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Support Recovery in the Phase Retrieval Model: Information-Theoretic Fundamental Limit.
IEEE Trans. Inf. Theory, 2020

Noisy Non-Adaptive Group Testing: A (Near-)Definite Defectives Approach.
IEEE Trans. Inf. Theory, 2020

On the All-or-Nothing Behavior of Bernoulli Group Testing.
IEEE J. Sel. Areas Inf. Theory, 2020

Information-Theoretic Lower Bounds for Compressive Sensing With Generative Models.
IEEE J. Sel. Areas Inf. Theory, 2020

Information-Theoretic Foundations of Mismatched Decoding.
Found. Trends Commun. Inf. Theory, 2020

On Gap-Based Lower Bounding Techniques for Best-Arm Identification.
Entropy, 2020

Non-Adaptive Group Testing in the Linear Regime: Strong Converse and Approximate Recovery.
CoRR, 2020

Improved Bounds and Algorithms for Sparsity-Constrained Group Testing.
CoRR, 2020

On the All-Or-Nothing Behavior of Bernoulli Group Testing.
CoRR, 2020

Sample Complexity Lower Bounds for Compressive Sensing with Generative Models.
Proceedings of the International Conference on Signal Processing and Communications, 2020

The Generalized Lasso with Nonlinear Observations and Generative Priors.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Near-Optimal Sparse Adaptive Group Testing.
Proceedings of the IEEE International Symposium on Information Theory, 2020

Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors.
Proceedings of the 37th International Conference on Machine Learning, 2020

A Characteristic Function Approach to Deep Implicit Generative Modeling.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

A Fast Binary Splitting Approach to Non-Adaptive Group Testing.
Proceedings of the Approximation, 2020

Learning Gaussian Graphical Models via Multiplicative Weights.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Corruption-Tolerant Gaussian Process Bandit Optimization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

A MaxSAT-Based Framework for Group Testing.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Generalized Random Gilbert-Varshamov Codes.
IEEE Trans. Inf. Theory, 2019

Noisy Adaptive Group Testing: Bounds and Algorithms.
IEEE Trans. Inf. Theory, 2019

Performance of Group Testing Algorithms With Near-Constant Tests Per Item.
IEEE Trans. Inf. Theory, 2019

Group Testing: An Information Theory Perspective.
Found. Trends Commun. Inf. Theory, 2019

Support Recovery in the Phase Retrieval Model: Information-Theoretic Fundamental Limits.
CoRR, 2019

An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation.
CoRR, 2019

Learning Erdos-Renyi Random Graphs via Edge Detecting Queries.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On the Information-Theoretic Limits of Noisy Sparse Phase Retrieval.
Proceedings of the 2019 IEEE Information Theory Workshop, 2019

A Recursive Cost-Constrained Construction that Attains the Expurgated Exponent.
Proceedings of the IEEE International Symposium on Information Theory, 2019

Overlapping Multi-Bandit Best Arm Identification.
Proceedings of the IEEE International Symposium on Information Theory, 2019

An Efficient Algorithm for Capacity-Approaching Noisy Adaptive Group Testing.
Proceedings of the IEEE International Symposium on Information Theory, 2019

Cross-sender bit-mixing coding.
Proceedings of the 18th International Conference on Information Processing in Sensor Networks, 2019

2018
Learning-Based Compressive MRI.
IEEE Trans. Medical Imaging, 2018

Mismatched Multi-Letter Successive Decoding for the Multiple-Access Channel.
IEEE Trans. Inf. Theory, 2018

Near-Optimal Noisy Group Testing via Separate Decoding of Items.
IEEE J. Sel. Top. Signal Process., 2018

Adversarially Robust Optimization with Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

The Error Exponent of Generalized Random-Gilbert Varshamov Codes.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Tight Regret Bounds for Bayesian Optimization in One Dimension.
Proceedings of the 35th International Conference on Machine Learning, 2018

The error exponent of random gilbert-varshamov codes.
Proceedings of the 52nd Annual Conference on Information Sciences and Systems, 2018

High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
The Dispersion of Nearest-Neighbor Decoding for Additive Non-Gaussian Channels.
IEEE Trans. Inf. Theory, 2017

Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework.
IEEE Trans. Inf. Theory, 2017

Efficient and Near-Optimal Noisy Group Testing: An Information-Theoretic Framework.
CoRR, 2017

An adaptive sublinear-time block sparse fourier transform.
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

Phase Transitions in the Pooled Data Problem.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Expurgated joint source-channel coding bounds and error exponents.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Robust Submodular Maximization: A Non-Uniform Partitioning Approach.
Proceedings of the 34th International Conference on Machine Learning, 2017

How little does non-exact recovery help in group testing?
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization.
Proceedings of the 30th Conference on Learning Theory, 2017

A distributed algorithm for partitioned robust submodular maximization.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

Lower Bounds on Active Learning for Graphical Model Selection.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
On the Difficulty of Selecting Ising Models With Approximate Recovery.
IEEE Trans. Signal Inf. Process. over Networks, 2016

Multiuser Random Coding Techniques for Mismatched Decoding.
IEEE Trans. Inf. Theory, 2016

Learning-Based Compressive Subsampling.
IEEE J. Sel. Top. Signal Process., 2016

Performance of group testing algorithms with constant tests-per-item.
CoRR, 2016

Phase Transitions in Group Testing.
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Converse bounds for noisy group testing with arbitrary measurement matrices.
Proceedings of the IEEE International Symposium on Information Theory, 2016

Partial recovery bounds for the sparse stochastic block model.
Proceedings of the IEEE International Symposium on Information Theory, 2016

Improved group testing rates with constant column weight designs.
Proceedings of the IEEE International Symposium on Information Theory, 2016

Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Time-Varying Gaussian Process Bandit Optimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Second-Order Asymptotics for the Gaussian MAC With Degraded Message Sets.
IEEE Trans. Inf. Theory, 2015

A Counter-Example to the Mismatched Decoding Converse for Binary-Input Discrete Memoryless Channels.
IEEE Trans. Inf. Theory, 2015

Second-Order Rate Region of Constant-Composition Codes for the Multiple-Access Channel.
IEEE Trans. Inf. Theory, 2015

On the Dispersions of the Gel'fand-Pinsker Channel and Dirty Paper Coding.
IEEE Trans. Inf. Theory, 2015

Limits on Support Recovery with Probabilistic Models: An Information-Spectrum Approach.
CoRR, 2015

Second-order asymptotics for the discrete memoryless MAC with degraded message sets.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Refinements of the third-order term in the fixed error asymptotics of constant-composition codes.
Proceedings of the IEEE International Symposium on Information Theory, 2015

The likelihood decoder: Error exponents and mismatch.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Active learning of self-concordant like multi-index functions.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Sparsistency of 1-Regularized M-Estimators.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Expurgated Random-Coding Ensembles: Exponents, Refinements, and Connections.
IEEE Trans. Inf. Theory, 2014

Mismatched Decoding: Error Exponents, Second-Order Rates and Saddlepoint Approximations.
IEEE Trans. Inf. Theory, 2014

The Saddlepoint Approximation: A Unification of Exponents, Dispersions and Moderate Deviations.
CoRR, 2014

A complex-integration approach to the saddlepoint approximation for random-coding bounds.
Proceedings of the 11th International Symposium on Wireless Communications Systems, 2014

The saddlepoint approximation: Unified random coding asymptotics for fixed and varying rates.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

On the dispersion of dirty paper coding.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

2013
Compressed Sensing With Prior Information: Information-Theoretic Limits and Practical Decoders.
IEEE Trans. Signal Process., 2013

Mismatched Decoding: Finite-Length Bounds, Error Exponents and Approximations
CoRR, 2013

Multiuser Coding Techniques for Mismatched Decoding.
CoRR, 2013

Second-Order Rate of Constant-Composition Codes for the Gel'fand-Pinsker Channel.
CoRR, 2013

Cost-constrained random coding and applications.
Proceedings of the 2013 Information Theory and Applications Workshop, 2013

The mismatched multiple-access channel: General alphabets.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Superposition codes for mismatched decoding.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

A derivation of the asymptotic random-coding prefactor.
Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012
Ensemble-tight error exponents for mismatched decoders.
Proceedings of the 50th Annual Allerton Conference on Communication, 2012

An achievable error exponent for the mismatched multiple-access channel.
Proceedings of the 50th Annual Allerton Conference on Communication, 2012

2011
On the Tradeoff Between Multiuser Diversity and Training Overhead in Multiple Access Channels
CoRR, 2011

How much training is needed in fading multiple access channels?
Proceedings of the 8th International Symposium on Wireless Communication Systems, 2011


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