Shubhanshu Shekhar

IEEE Trans. Inf. Theory, February, 2024

Reducing sequential change detection to sequential estimation.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Deep anytime-valid hypothesis testing.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

A Permutation-Free Kernel Independence Test.

[BibT_eX]

[DOI]

Ilmun Kim

J. Mach. Learn. Res., 2023

On the near-optimality of betting confidence sets for bounded means.

[BibT_eX]

[DOI]

CoRR, 2023

Sequential change detection via backward confidence sequences.

[BibT_eX]

[DOI]

CoRR, 2023

Risk-limiting financial audits via weighted sampling without replacement.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Sequential Changepoint Detection via Backward Confidence Sequences.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

A permutation-free kernel two-sample test.

[BibT_eX]

[DOI]

Ilmun Kim

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multi-Scale Zero-Order Optimization of Smooth Functions in an RKHS.

[BibT_eX]

[DOI]

Madison Lee

Proceedings of the IEEE International Symposium on Information Theory, 2022

Instance Dependent Regret Analysis of Kernelized Bandits.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

Active Learning for Classification With Abstention.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Inf. Theory, 2021

Game-theoretic Formulations of Sequential Nonparametric One- and Two-Sample Tests.

[BibT_eX]

[DOI]

CoRR, 2021

Uncertainty-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric.

[BibT_eX]

[DOI]

Dawei Sun

Mohammad Javad Khojasteh

Chuchu Fan

CoRR, 2021

Adaptive Sampling for Minimax Fair Classification.

[BibT_eX]

[DOI]

CoRR, 2021

Adaptive Sampling for Minimax Fair Classification.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric.

[BibT_eX]

[DOI]

Dawei Sun

Mohammad Javad Khojasteh

Chuchu Fan

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Significance of Gradient Information in Bayesian Optimization.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Multi-Scale Zero-Order Optimization of Smooth Functions in an RKHS.

[BibT_eX]

[DOI]

CoRR, 2020

Active Model Estimation in Markov Decision Processes.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Adaptive Sampling for Estimating Probability Distributions.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Adaptive Sampling for Estimating Multiple Probability Distributions.

[BibT_eX]

[DOI]

CoRR, 2019

Active Learning for Binary Classification with Abstention.

[BibT_eX]

[DOI]

CoRR, 2019

Binary Classification with Bounded Abstention Rate.

[BibT_eX]

[DOI]

CoRR, 2019

Multiscale Gaussian Process Level Set Estimation.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Species Tree Estimation Using ASTRAL: How Many Genes Are Enough?

[BibT_eX]

[DOI]

Sebastien Roch

Siavash Mirarab

IEEE ACM Trans. Comput. Biol. Bioinform., 2018

2017

Gaussian Process bandits with adaptive discretization.

[BibT_eX]

[DOI]

CoRR, 2017

Bayesian function optimization with adaptive discretization.

[BibT_eX]

[DOI]