How much training is needed in fading multiple access channels? - Jonathan Scarlett; Jamie S. Evans; Subhrakanti Dey (ISWCS, 2011)

On the Tradeoff Between Multiuser Diversity and Training Overhead in Multiple Access Channels - Jonathan Scarlett; Jamie S. Evans; Subhrakanti Dey (CoRR, 2011)

An achievable error exponent for the mismatched multiple-access channel. - Jonathan Scarlett; Albert Guillen i Fabregas (Allerton Conference, 2012)

Ensemble-tight error exponents for mismatched decoders. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (Allerton Conference, 2012)

Second-order rate region of constant-composition codes for the multiple-access channel. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (Allerton, 2013)

A derivation of the asymptotic random-coding prefactor. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (Allerton, 2013)

Superposition codes for mismatched decoding. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (ISIT, 2013)

The mismatched multiple-access channel: General alphabets. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (ISIT, 2013)

Cost-constrained random coding and applications. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (ITA, 2013)

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

Multiuser Coding Techniques for Mismatched Decoding. - Jonathan Scarlett; Alfonso Martinez; Albert Guillén i Fàbregas (CoRR, 2013)

Mismatched Decoding: Finite-Length Bounds, Error Exponents and Approximations - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (CoRR, 2013)

Compressed Sensing With Prior Information: Information-Theoretic Limits and Practical Decoders. - Jonathan Scarlett; Jamie S. Evans; Subhrakanti Dey (IEEE Trans. Signal Process., 2013)

On the dispersion of dirty paper coding. - Jonathan Scarlett (ISIT, 2014)

The saddlepoint approximation: Unified random coding asymptotics for fixed and varying rates. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (ISIT, 2014)

Mismatched multi-letter successive decoding for the multiple-access channel. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (ISIT, 2014)

Second-order asymptotics for the gaussian MAC with degraded message sets. - Jonathan Scarlett; Vincent Y. F. Tan (ISIT, 2014)

A complex-integration approach to the saddlepoint approximation for random-coding bounds. - Alfonso Martinez; Jonathan Scarlett; Marco Dalai; Albert Guillen i Fabregas (ISWCS, 2014)

The Saddlepoint Approximation: A Unification of Exponents, Dispersions and Moderate Deviations. - Jonathan Scarlett; Alfonso Martinez; Albert Guillén i Fàbregas (CoRR, 2014)

Mismatched Decoding: Error Exponents, Second-Order Rates and Saddlepoint Approximations. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (IEEE Trans. Inf. Theory, 2014)

Expurgated Random-Coding Ensembles: Exponents, Refinements, and Connections. - Jonathan Scarlett; Li Peng 001; Neri Merhav; Alfonso Martinez; Albert Guillen i Fabregas (IEEE Trans. Inf. Theory, 2014)

Sparsistency of 1-Regularized M-Estimators. - Yen-Huan Li; Jonathan Scarlett; Pradeep Ravikumar; Volkan Cevher (AISTATS, 2015)

Active learning of self-concordant like multi-index functions. - Ilija Bogunovic; Volkan Cevher; Jarvis D. Haupt; Jonathan Scarlett (ICASSP, 2015)

Limits on support recovery with probabilistic models: An information-theoretic framework. - Jonathan Scarlett; Volkan Cevher (ISIT, 2015)

The likelihood decoder: Error exponents and mismatch. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (ISIT, 2015)

Refinements of the third-order term in the fixed error asymptotics of constant-composition codes. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (ISIT, 2015)

Second-order asymptotics for the discrete memoryless MAC with degraded message sets. - Jonathan Scarlett; Vincent Y. F. Tan (ISIT, 2015)

Limits on Support Recovery with Probabilistic Models: An Information-Spectrum Approach. - Jonathan Scarlett; Volkan Cevher (CoRR, 2015)

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

A Counter-Example to the Mismatched Decoding Converse for Binary-Input Discrete Memoryless Channels. - Jonathan Scarlett; Anelia Somekh-Baruch; Alfonso Martinez; Albert Guillen i Fabregas (IEEE Trans. Inf. Theory, 2015)

Time-Varying Gaussian Process Bandit Optimization. - Ilija Bogunovic; Jonathan Scarlett; Volkan Cevher (AISTATS, 2016)

Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices. - Jonathan Scarlett; Volkan Cevher (AISTATS, 2016)

Improved group testing rates with constant column weight designs. - Matthew Aldridge; Oliver Johnson; Jonathan Scarlett (ISIT, 2016)

Partial recovery bounds for the sparse stochastic block model. - Jonathan Scarlett; Volkan Cevher (ISIT, 2016)

Converse bounds for noisy group testing with arbitrary measurement matrices. - Jonathan Scarlett; Volkan Cevher (ISIT, 2016)

The dispersion of nearest-neighbor decoding for additive non-Gaussian channels. - Jonathan Scarlett; Vincent Y. F. Tan; Giuseppe Durisi (ISIT, 2016)

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation. - Ilija Bogunovic; Jonathan Scarlett; Andreas Krause 001; Volkan Cevher (NIPS, 2016)

Phase Transitions in Group Testing. - Jonathan Scarlett; Volkan Cevher (SODA, 2016)

Performance of group testing algorithms with constant tests-per-item. - Oliver Johnson; Matthew Aldridge; Jonathan Scarlett (CoRR, 2016)

Learning-Based Compressive Subsampling. - Luca Baldassarre; Yen-Huan Li; Jonathan Scarlett; Baran Gozcu; Ilija Bogunovic; Volkan Cevher (IEEE J. Sel. Top. Signal Process., 2016)

Multiuser Random Coding Techniques for Mismatched Decoding. - Jonathan Scarlett; Alfonso Martinez; Albert Guillén i Fàbregas (IEEE Trans. Inf. Theory, 2016)

On the Difficulty of Selecting Ising Models With Approximate Recovery. - Jonathan Scarlett; Volkan Cevher (IEEE Trans. Signal Inf. Process. over Networks, 2016)

Lower Bounds on Active Learning for Graphical Model Selection. - Jonathan Scarlett; Volkan Cevher (AISTATS, 2017)

A distributed algorithm for partitioned robust submodular maximization. - Ilija Bogunovic; Slobodan Mitrovic; Jonathan Scarlett; Volkan Cevher (CAMSAP, 2017)

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization. - Jonathan Scarlett; Ilija Bogunovic; Volkan Cevher (COLT, 2017)

How little does non-exact recovery help in group testing? - Jonathan Scarlett; Volkan Cevher (ICASSP, 2017)

Robust Submodular Maximization: A Non-Uniform Partitioning Approach. - Ilija Bogunovic; Slobodan Mitrovic; Jonathan Scarlett; Volkan Cevher (ICML, 2017)

Expurgated joint source-channel coding bounds and error exponents. - Jonathan Scarlett; Alfonso Martinez; Albert Guillen i Fabregas (ISIT, 2017)

Phase Transitions in the Pooled Data Problem. - Jonathan Scarlett; Volkan Cevher (NIPS, 2017)

An adaptive sublinear-time block sparse fourier transform. - Volkan Cevher; Michael Kapralov; Jonathan Scarlett; Amir Zandieh (STOC, 2017)

Efficient and Near-Optimal Noisy Group Testing: An Information-Theoretic Framework. - Jonathan Scarlett; Volkan Cevher (CoRR, 2017)

High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups. - Paul Rolland; Jonathan Scarlett; Ilija Bogunovic; Volkan Cevher (AISTATS, 2018)

The error exponent of random gilbert-varshamov codes. - Anelia Somekh-Baruch; Jonathan Scarlett; Albert Guillen i Fabregas (CISS, 2018)

Tight Regret Bounds for Bayesian Optimization in One Dimension. - Jonathan Scarlett (ICML, 2018)

Near-Optimal Noisy Group Testing via Separate Decoding of Items. - Jonathan Scarlett; Volkan Cevher (ISIT, 2018)

The Error Exponent of Generalized Random-Gilbert Varshamov Codes. - Anelia Somekh-Baruch; Jonathan Scarlett; Albert Guillen i Fabregas (ISIT, 2018)

Adversarially Robust Optimization with Gaussian Processes. - Ilija Bogunovic; Jonathan Scarlett; Stefanie Jegelka; Volkan Cevher (NeurIPS, 2018)

Learning-Based Compressive MRI. - Baran Gozcu; Rabeeh Karimi Mahabadi; Yen-Huan Li; Efe Ilicak; Tolga Çukur; Jonathan Scarlett; Volkan Cevher (IEEE Trans. Medical Imaging, 2018)

Cross-sender bit-mixing coding. - Steffen Bondorf; Binbin Chen 001; Jonathan Scarlett; Haifeng Yu; Yuda Zhao (IPSN, 2019)

An Efficient Algorithm for Capacity-Approaching Noisy Adaptive Group Testing. - Jonathan Scarlett (ISIT, 2019)

Overlapping Multi-Bandit Best Arm Identification. - Jonathan Scarlett; Ilija Bogunovic; Volkan Cevher (ISIT, 2019)

A Recursive Cost-Constrained Construction that Attains the Expurgated Exponent. - Anelia Somekh-Baruch; Jonathan Scarlett; Albert Guillén i Fàbregas (ISIT, 2019)

On the Information-Theoretic Limits of Noisy Sparse Phase Retrieval. - Lan V. Truong; Jonathan Scarlett (ITW, 2019)

Learning Erdos-Renyi Random Graphs via Edge Detecting Queries. - Zihan Li; Matthias Fresacher; Jonathan Scarlett (NeurIPS, 2019)

An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation. - Jonathan Scarlett; Volkan Cevher (CoRR, 2019)

Support Recovery in the Phase Retrieval Model: Information-Theoretic Fundamental Limits. - Lan V. Truong; Jonathan Scarlett (CoRR, 2019)

Group Testing: An Information Theory Perspective. - Matthew Aldridge; Oliver Johnson; Jonathan Scarlett (Found. Trends Commun. Inf. Theory, 2019)

Performance of Group Testing Algorithms With Near-Constant Tests Per Item. - Oliver Johnson; Matthew Aldridge; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2019)

Noisy Adaptive Group Testing: Bounds and Algorithms. - Jonathan Scarlett (IEEE Trans. Inf. Theory, 2019)

Generalized Random Gilbert-Varshamov Codes. - Anelia Somekh-Baruch; Jonathan Scarlett; Albert Guillen i Fabregas (IEEE Trans. Inf. Theory, 2019)

A MaxSAT-Based Framework for Group Testing. - Lorenzo Ciampiconi; Bishwamittra Ghosh; Jonathan Scarlett; Kuldeep S. Meel (AAAI, 2020)

Corruption-Tolerant Gaussian Process Bandit Optimization. - Ilija Bogunovic; Andreas Krause 001; Jonathan Scarlett (AISTATS, 2020)

Learning Gaussian Graphical Models via Multiplicative Weights. - Anamay Chaturvedi; Jonathan Scarlett (AISTATS, 2020)

A Fast Binary Splitting Approach to Non-Adaptive Group Testing. - Eric Price 001; Jonathan Scarlett (APPROX-RANDOM, 2020)

A Characteristic Function Approach to Deep Implicit Generative Modeling. - Abdul Fatir Ansari; Jonathan Scarlett; Harold Soh (CVPR, 2020)

Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors. - Zhaoqiang Liu; Selwyn Gomes; Avtansh Tiwari; Jonathan Scarlett (ICML, 2020)

Near-Optimal Sparse Adaptive Group Testing. - Nelvin Tan; Jonathan Scarlett (ISIT, 2020)

The Generalized Lasso with Nonlinear Observations and Generative Priors. - Zhaoqiang Liu; Jonathan Scarlett (NeurIPS, 2020)

Sample Complexity Lower Bounds for Compressive Sensing with Generative Models. - Zhaoqiang Liu; Jonathan Scarlett (SPCOM, 2020)

On the All-Or-Nothing Behavior of Bernoulli Group Testing. - Lan V. Truong; Jonathan Scarlett (CoRR, 2020)

Improved Bounds and Algorithms for Sparsity-Constrained Group Testing. - Nelvin Tan; Jonathan Scarlett (CoRR, 2020)

Non-Adaptive Group Testing in the Linear Regime: Strong Converse and Approximate Recovery. - Bay Wei Heng; Jonathan Scarlett (CoRR, 2020)

On Gap-Based Lower Bounding Techniques for Best-Arm Identification. - Lan V. Truong; Jonathan Scarlett (Entropy, 2020)

Information-Theoretic Foundations of Mismatched Decoding. - Jonathan Scarlett; Albert Guillén i Fàbregas; Anelia Somekh-Baruch; Alfonso Martinez (Found. Trends Commun. Inf. Theory, 2020)

Information-Theoretic Lower Bounds for Compressive Sensing With Generative Models. - Zhaoqiang Liu; Jonathan Scarlett (IEEE J. Sel. Areas Inf. Theory, 2020)

On the All-or-Nothing Behavior of Bernoulli Group Testing. - Lan V. Truong; Matthew Aldridge; Jonathan Scarlett (IEEE J. Sel. Areas Inf. Theory, 2020)

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

Support Recovery in the Phase Retrieval Model: Information-Theoretic Fundamental Limit. - Lan V. Truong; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2020)

High-Dimensional Bayesian Optimization via Tree-Structured Additive Models. - Eric Han; Ishank Arora; Jonathan Scarlett (AAAI, 2021)

Stochastic Linear Bandits Robust to Adversarial Attacks. - Ilija Bogunovic; Arpan Losalka; Andreas Krause 001; Jonathan Scarlett (AISTATS, 2021)

Open Problem: Tight Online Confidence Intervals for RKHS Elements. - Sattar Vakili; Jonathan Scarlett; Tara Javidi (COLT, 2021)

Lenient Regret and Good-Action Identification in Gaussian Process Bandits. - Xu Cai; Selwyn Gomes; Jonathan Scarlett (ICML, 2021)

On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization. - Xu Cai; Jonathan Scarlett (ICML, 2021)

Optimal Rates of Teaching and Learning Under Binary Symmetric Noise. - Yan Hao Ling; Jonathan Scarlett (ISIT, 2021)

An Analysis of the DD Algorithm for Group Testing with Size-Constrained Tests. - Nelvin Tan; Jonathan Scarlett (ISIT, 2021)

Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors. - Zhaoqiang Liu; Subhroshekhar Ghosh; Jonathan Scarlett (ITW, 2021)

Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors. - Zhaoqiang Liu; Subhroshekhar Ghosh; Jonathan Scarlett (NeurIPS, 2021)

Fast Splitting Algorithms for Sparsity-Constrained and Noisy Group Testing. - Eric Price 001; Jonathan Scarlett; Nelvin Tan (CoRR, 2021)

Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors. - Zhaoqiang Liu; Subhroshekhar Ghosh; Jun Han; Jonathan Scarlett (CoRR, 2021)

On Architecture Selection for Linear Inverse Problems with Untrained Neural Networks. - Yang Sun; Hangdong Zhao; Jonathan Scarlett (Entropy, 2021)

Sublinear-Time Non-Adaptive Group Testing With O(k log n) Tests via Bit-Mixing Coding. - Steffen Bondorf; Binbin Chen 001; Jonathan Scarlett; Haifeng Yu; Yuda Zhao (IEEE Trans. Inf. Theory, 2021)

Optimal Rates of Teaching and Learning Under Uncertainty. - Yan Hao Ling; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2021)

Max-Min Grouped Bandits. - Zhenlin Wang; Jonathan Scarlett (AAAI, 2022)

Gaussian Process Bandit Optimization with Few Batches. - Zihan Li; Jonathan Scarlett (AISTATS, 2022)

Data-Driven Algorithms for Gaussian Measurement Matrix Design in Compressive Sensing. - Yang Sun; Jonathan Scarlett (ICASSP, 2022)

Generative Principal Component Analysis. - Zhaoqiang Liu; Jiulong Liu; Subhroshekhar Ghosh; Jun Han; Jonathan Scarlett (ICLR, 2022)

Adversarial Attacks on Gaussian Process Bandits. - Eric Han; Jonathan Scarlett (ICML, 2022)

Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning. - Sattar Vakili; Jonathan Scarlett; Da-Shan Shiu; Alberto Bernacchia (ICML, 2022)

Universal 1-Bit Compressive Sensing for Bounded Dynamic Range Signals. - Sidhant Bansal; Arnab Bhattacharyya 001; Anamay Chaturvedi; Jonathan Scarlett (ISIT, 2022)

Group Testing with Blocks of Positives. - Thach V. Bui; Yeow Meng Chee; Jonathan Scarlett; Van Khu Vu (ISIT, 2022)

Multi-User Random Coding Techniques for Mismatched Rate-Distortion Theory. - Millen Kanabar; Jonathan Scarlett (ISIT, 2022)

A Simple Coding Scheme Attaining Positive Information Velocity. - Yan Hao Ling; Jonathan Scarlett (ISIT, 2022)

A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits. - Ilija Bogunovic; Zihan Li; Andreas Krause 001; Jonathan Scarlett (NeurIPS, 2022)

Order-Optimal Error Bounds for Noisy Kernel-Based Bayesian Quadrature. - Xu Cai; Chi Thanh Lam; Jonathan Scarlett (CoRR, 2022)

Near-Optimal Sparsity-Constrained Group Testing: Improved Bounds and Algorithms. - Oliver Gebhard; Max Hahn-Klimroth; Olaf Parczyk; Manuel Penschuck; Maurice Rolvien; Jonathan Scarlett; Nelvin Tan (IEEE Trans. Inf. Theory, 2022)

Simple Coding Techniques for Many-Hop Relaying. - Yan Hao Ling; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2022)

Noisy Adaptive Group Testing via Noisy Binary Search. - Bernard Teo; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2022)

Model-Based and Graph-Based Priors for Group Testing. - Ivan Lau; Jonathan Scarlett; Yang Sun (IEEE Trans. Signal Process., 2022)

Tight Regret Bounds for Noisy Optimization of a Brownian Motion. - Zexin Wang 002; Vincent Y. F. Tan; Jonathan Scarlett (IEEE Trans. Signal Process., 2022)

Guest Editorial. - Paul Hand; Reinhard Heckel; Jonathan Scarlett (IEEE J. Sel. Areas Inf. Theory, 2022)

Theoretical Perspectives on Deep Learning Methods in Inverse Problems. - Jonathan Scarlett; Reinhard Heckel; Miguel R. D. Rodrigues; Paul Hand; Yonina C. Eldar (IEEE J. Sel. Areas Inf. Theory, 2022)

Max-Quantile Grouped Infinite-Arm Bandits. - Ivan Lau; Yan Hao Ling; Mayank Shrivastava; Jonathan Scarlett (ALT, 2023)

For One and All: Individual and Group Fairness in the Allocation of Indivisible Goods. - Jonathan Scarlett; Nicholas Teh; Yair Zick (AAMAS, 2023)

Communication-Constrained Bandits under Additive Gaussian Noise. - Prathamesh Mayekar; Jonathan Scarlett; Vincent Y. F. Tan (ICML, 2023)

A Unified Framework for Uniform Signal Recovery in Nonlinear Generative Compressed Sensing. - Junren Chen; Jonathan Scarlett; Michael Ng 001; Zhaoqiang Liu (NeurIPS, 2023)

Benefits of monotonicity in safe exploration with Gaussian processes. - Arpan Losalka; Jonathan Scarlett (UAI, 2023)

Approximate Message Passing with Rigorous Guarantees for Pooled Data and Quantitative Group Testing. - Nelvin Tan; Jonathan Scarlett; Ramji Venkataramanan (CoRR, 2023)

On Average-Case Error Bounds for Kernel-Based Bayesian Quadrature. - Xu Cai; Chi Thanh Lam; Jonathan Scarlett (Trans. Mach. Learn. Res., 2023)

Performance Bounds for Group Testing With Doubly-Regular Designs. - Nelvin Tan; Way Tan; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2023)

Multi-Bit Relaying Over a Tandem of Channels. - Yan Hao Ling; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2023)

Kernelized Normalizing Constant Estimation: Bridging Bayesian Quadrature and Bayesian Optimization. - Xu Cai; Jonathan Scarlett (AAAI, 2024)

No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints. - Arpan Losalka; Jonathan Scarlett (AISTATS, 2024)

Exact Error Exponents for a Concatenated Coding Based Class of DNA Storage Codes. - Yan Hao Ling; Jonathan Scarlett (ISIT, 2024)

Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization. - Qianli Shen; Yezhen Wang; Zhouhao Yang; Xiang Li; Haonan Wang; Yang Zhang; Jonathan Scarlett; Zhanxing Zhu; Kenji Kawaguchi (NeurIPS, 2024)

Complexity of Round-Robin Allocation with Potentially Noisy Queries. - Zihan Li; Pasin Manurangsi; Jonathan Scarlett; Warut Suksompong (SAGT, 2024)

Robust Instance Optimal Phase-Only Compressed Sensing. - Junren Chen; Zhaoqiang Liu; Michael Kwok-Po Ng; Jonathan Scarlett (CoRR, 2024)

Approximate Message Passing with Rigorous Guarantees for Pooled Data and Quantitative Group Testing. - Nelvin Tan; Pablo Pascual Cobo; Jonathan Scarlett; Ramji Venkataramanan (SIAM J. Math. Data Sci., 2024)

Mismatched Rate-Distortion Theory: Ensembles, Bounds, and General Alphabets. - Millen Kanabar; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2024)

Regret Bounds for Noise-Free Cascaded Kernelized Bandits. - Zihan Li; Jonathan Scarlett (Trans. Mach. Learn. Res., 2024)

Maxflow-Based Bounds for Low-Rate Information Propagation Over Noisy Networks. - Yan Hao Ling; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2024)

Concomitant Group Testing. - Thach V. Bui; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2024)

Optimal 1-bit Error Exponent for 2-Hop Relaying With Binary-Input Channels. - Yan Hao Ling; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2024)

Lower Bounds for Time-Varying Kernelized Bandits. - Xu Cai; Jonathan Scarlett (AISTATS, 2025)

Quantile Multi-Armed Bandits with 1-bit Feedback. - Ivan Lau; Jonathan Scarlett (ALT, 2025)

A General Framework for Clustering and Distribution Matching with Bandit Feedback. - Recep Can Yavas; Yuqi Huang; Vincent Y. F. Tan; Jonathan Scarlett (ISIT, 2025)

Exact Thresholds for Noisy Non-Adaptive Group Testing. - Junren Chen; Jonathan Scarlett (SODA, 2025)

Error Exponents for DNA Storage Codes With a Variable Number of Reads. - Yan Hao Ling; Nir Weinberger; Jonathan Scarlett (IEEE J. Sel. Areas Inf. Theory, 2025)

Statistical Mean Estimation with Coded Relayed Observations. - Yan Hao Ling; Zhouhao Yang; Jonathan Scarlett (CoRR, 2025)

Improved Regret Bounds for Linear Bandits with Heavy-Tailed Rewards. - Artin Tajdini; Jonathan Scarlett; Kevin G. Jamieson (CoRR, 2025)

Optimal Non-Adaptive Group Testing with One-Sided Error Guarantees. - Daniel McMorrow; Jonathan Scarlett (CoRR, 2025)

Sequential 1-bit Mean Estimation with Near-Optimal Sample Complexity. - Ivan Lau; Jonathan Scarlett (CoRR, 2025)

Exact Error Exponents of Concatenated Codes for DNA Storage. - Yan Hao Ling; Jonathan Scarlett (IEEE Trans. Inf. Theory, 2025)