Shubhanshu Shekhar

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 37

Top Topics

Gaussian Process

Top Venues

Publications

Shubhanshu Shekhar, Aaditya Ramdas
Nonparametric Two-Sample Testing by Betting. IEEE Trans. Inf. Theory 70 (2) (2024)
Teodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar
Deep anytime-valid hypothesis testing. AISTATS (2024)
Shubhanshu Shekhar, Ziyu Xu, Zachary C. Lipton, Pierre J. Liang, Aaditya Ramdas
Risk-limiting Financial Audits via Weighted Sampling without Replacement. CoRR (2023)
Teodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar
Deep anytime-valid hypothesis testing. CoRR (2023)
Shubhanshu Shekhar, Aaditya Ramdas
Sequential Changepoint Detection via Backward Confidence Sequences. ICML (2023)
Shubhanshu Shekhar, Ziyu Xu, Zachary C. Lipton, Pierre J. Liang, Aaditya Ramdas
Risk-limiting financial audits via weighted sampling without replacement. UAI (2023)
Shubhanshu Shekhar, Aaditya Ramdas
On the near-optimality of betting confidence sets for bounded means. CoRR (2023)
Shubhanshu Shekhar, Aaditya Ramdas
Reducing sequential change detection to sequential estimation. CoRR (2023)
Shubhanshu Shekhar, Aaditya Ramdas
Sequential change detection via backward confidence sequences. CoRR (2023)
Shubhanshu Shekhar, Tara Javidi
Instance Dependent Regret Analysis of Kernelized Bandits. ICML (2022)
Madison Lee, Shubhanshu Shekhar, Tara Javidi
Multi-Scale Zero-Order Optimization of Smooth Functions in an RKHS. ISIT (2022)
Shubhanshu Shekhar, Tara Javidi
Instance-Dependent Regret Analysis of Kernelized Bandits. CoRR (2022)
Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas
A Permutation-free Kernel Two-Sample Test. CoRR (2022)
Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas
A permutation-free kernel two-sample test. NeurIPS (2022)
Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas
A Permutation-Free Kernel Independence Test. CoRR (2022)
Shubhanshu Shekhar, Aaditya Ramdas
Game-theoretic Formulations of Sequential Nonparametric One- and Two-Sample Tests. CoRR (2021)
Dawei Sun, Mohammad Javad Khojasteh, Shubhanshu Shekhar, Chuchu Fan
Uncertainty-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric. CoRR (2021)
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
Adaptive Sampling for Minimax Fair Classification. CoRR (2021)
Shubhanshu Shekhar, Tara Javidi
Significance of Gradient Information in Bayesian Optimization. AISTATS (2021)
Shubhanshu Shekhar, Greg Fields, Mohammad Ghavamzadeh, Tara Javidi
Adaptive Sampling for Minimax Fair Classification. NeurIPS (2021)
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
Active Learning for Classification With Abstention. IEEE J. Sel. Areas Inf. Theory 2 (2) (2021)
Dawei Sun, Mohammad Javad Khojasteh, Shubhanshu Shekhar, Chuchu Fan
Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric. L4DC (2021)
Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric
Active Model Estimation in Markov Decision Processes. CoRR (2020)
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
Active Learning for Classification with Abstention. ISIT (2020)
Shubhanshu Shekhar, Tara Javidi
Multi-Scale Zero-Order Optimization of Smooth Functions in an RKHS. CoRR (2020)
Shubhanshu Shekhar, Tara Javidi, Mohammad Ghavamzadeh
Adaptive Sampling for Estimating Probability Distributions. ICML (2020)
Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric
Active Model Estimation in Markov Decision Processes. UAI (2020)
Shubhanshu Shekhar, Tara Javidi
Multiscale Gaussian Process Level Set Estimation. AISTATS (2019)
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
Binary Classification with Bounded Abstention Rate. CoRR (2019)
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
Active Learning for Binary Classification with Abstention. CoRR (2019)
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
Adaptive Sampling for Estimating Multiple Probability Distributions. CoRR (2019)
Shubhanshu Shekhar, Tara Javidi
Multiscale Gaussian Process Level Set Estimation. CoRR (2019)
Shubhanshu Shekhar, Sebastien Roch, Siavash Mirarab
Species Tree Estimation Using ASTRAL: How Many Genes Are Enough? IEEE ACM Trans. Comput. Biol. Bioinform. 15 (5) (2018)
Shubhanshu Shekhar, Tara Javidi
Bayesian function optimization with adaptive discretization. Allerton (2017)
Shubhanshu Shekhar, Tara Javidi
Gaussian Process bandits with adaptive discretization. CoRR (2017)
Shubhanshu Shekhar, Sebastien Roch, Siavash Mirarab
Species Tree Estimation Using ASTRAL: How Many Genes Are Enough? RECOMB (2017)
Shubhanshu Shekhar, Sebastien Roch, Siavash Mirarab
Species tree estimation using ASTRAL: how many genes are enough? CoRR (2017)