Shekhar, Shubhanshu

13 publications

AISTATS 2024 Deep Anytime-Valid Hypothesis Testing Teodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar

ICML 2024 Reducing Sequential Change Detection to Sequential Estimation Shubhanshu Shekhar, Aaditya Ramdas

JMLR 2023 A Permutation-Free Kernel Independence Test Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas

UAI 2023 Risk-Limiting Financial Audits via Weighted Sampling Without Replacement Shubhanshu Shekhar, Ziyu Xu, Zachary Lipton, Pierre Liang, Aaditya Ramdas

ICML 2023 Sequential Changepoint Detection via Backward Confidence Sequences Shubhanshu Shekhar, Aaditya Ramdas

NeurIPS 2022 A Permutation-Free Kernel Two-Sample Test Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas

ICML 2022 Instance Dependent Regret Analysis of Kernelized Bandits Shubhanshu Shekhar, Tara Javidi

AISTATS 2021 Significance of Gradient Information in Bayesian Optimization Shubhanshu Shekhar, Tara Javidi

NeurIPS 2021 Adaptive Sampling for Minimax Fair Classification Shubhanshu Shekhar, Greg Fields, Mohammad Ghavamzadeh, Tara Javidi

L4DC 2021 Uncertain-Aware Safe Exploratory Planning Using Gaussian Process and Neural Control Contraction Metric Dawei Sun, Mohammad Javad Khojasteh, Shubhanshu Shekhar, Chuchu Fan

UAI 2020 Active Model Estimation in Markov Decision Processes Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric

ICML 2020 Adaptive Sampling for Estimating Probability Distributions Shubhanshu Shekhar, Tara Javidi, Mohammad Ghavamzadeh

AISTATS 2019 Multiscale Gaussian Process Level Set Estimation Shubhanshu Shekhar, Tara Javidi