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ORCIDShubhanshu Shekhar
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2020 – today
- 2024
[j4]Shubhanshu Shekhar
, Aaditya Ramdas:
Nonparametric Two-Sample Testing by Betting. IEEE Trans. Inf. Theory 70(2): 1178-1203 (2024)- [c16]Teodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar:
Deep anytime-valid hypothesis testing. AISTATS 2024: 622-630 - [c15]Shubhanshu Shekhar, Aaditya Ramdas:
Reducing sequential change detection to sequential estimation. ICML 2024 - 2023
- [j3]Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas:
A Permutation-Free Kernel Independence Test. J. Mach. Learn. Res. 24: 369:1-369:68 (2023) - [c14]Shubhanshu Shekhar, Aaditya Ramdas:
Sequential Changepoint Detection via Backward Confidence Sequences. ICML 2023: 30908-30930 - [c13]Shubhanshu Shekhar, Ziyu Xu, Zachary C. Lipton, Pierre J. Liang, Aaditya Ramdas:
Risk-limiting financial audits via weighted sampling without replacement. UAI 2023: 1932-1941 - [i19]Shubhanshu Shekhar, Aaditya Ramdas:
Sequential change detection via backward confidence sequences. CoRR abs/2302.02544 (2023) - [i18]Shubhanshu Shekhar, Ziyu Xu, Zachary C. Lipton, Pierre J. Liang, Aaditya Ramdas:
Risk-limiting Financial Audits via Weighted Sampling without Replacement. CoRR abs/2305.06884 (2023) - [i17]Shubhanshu Shekhar, Aaditya Ramdas:
Reducing sequential change detection to sequential estimation. CoRR abs/2309.09111 (2023) - [i16]Shubhanshu Shekhar, Aaditya Ramdas:
On the near-optimality of betting confidence sets for bounded means. CoRR abs/2310.01547 (2023) - [i15]Teodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar:
Deep anytime-valid hypothesis testing. CoRR abs/2310.19384 (2023) - 2022
- [c12]Shubhanshu Shekhar, Tara Javidi:
Instance Dependent Regret Analysis of Kernelized Bandits. ICML 2022: 19747-19772 - [c11]Madison Lee, Shubhanshu Shekhar, Tara Javidi:
Multi-Scale Zero-Order Optimization of Smooth Functions in an RKHS. ISIT 2022: 288-293 - [c10]Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas:
A permutation-free kernel two-sample test. NeurIPS 2022 - [i14]Shubhanshu Shekhar, Tara Javidi:
Instance-Dependent Regret Analysis of Kernelized Bandits. CoRR abs/2203.06297 (2022) - [i13]Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas:
A Permutation-free Kernel Two-Sample Test. CoRR abs/2211.14908 (2022) - [i12]Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas:
A Permutation-Free Kernel Independence Test. CoRR abs/2212.09108 (2022) - 2021
- [j2]Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi:
Active Learning for Classification With Abstention. IEEE J. Sel. Areas Inf. Theory 2(2): 705-719 (2021) - [c9]Shubhanshu Shekhar, Tara Javidi:
Significance of Gradient Information in Bayesian Optimization. AISTATS 2021: 2836-2844 - [c8]Dawei Sun, Mohammad Javad Khojasteh, Shubhanshu Shekhar, Chuchu Fan:
Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric. L4DC 2021: 728-741 - [c7]Shubhanshu Shekhar, Greg Fields, Mohammad Ghavamzadeh, Tara Javidi:
Adaptive Sampling for Minimax Fair Classification. NeurIPS 2021: 24535-24544 - [i11]Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi:
Adaptive Sampling for Minimax Fair Classification. CoRR abs/2103.00755 (2021) - [i10]Dawei Sun, Mohammad Javad Khojasteh, Shubhanshu Shekhar, Chuchu Fan:
Uncertainty-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric. CoRR abs/2105.06567 (2021) - [i9]Shubhanshu Shekhar, Aaditya Ramdas:
Game-theoretic Formulations of Sequential Nonparametric One- and Two-Sample Tests. CoRR abs/2112.09162 (2021) - 2020
- [c6]Shubhanshu Shekhar, Tara Javidi, Mohammad Ghavamzadeh:
Adaptive Sampling for Estimating Probability Distributions. ICML 2020: 8687-8696 - [c5]Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi:
Active Learning for Classification with Abstention. ISIT 2020: 2801-2806 - [c4]Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric:
Active Model Estimation in Markov Decision Processes. UAI 2020: 1019-1028 - [i8]Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric:
Active Model Estimation in Markov Decision Processes. CoRR abs/2003.03297 (2020) - [i7]Shubhanshu Shekhar, Tara Javidi:
Multi-Scale Zero-Order Optimization of Smooth Functions in an RKHS. CoRR abs/2005.04832 (2020)
2010 – 2019
- 2019
- [c3]Shubhanshu Shekhar, Tara Javidi:
Multiscale Gaussian Process Level Set Estimation. AISTATS 2019: 3283-3291 - [i6]Shubhanshu Shekhar, Tara Javidi:
Multiscale Gaussian Process Level Set Estimation. CoRR abs/1902.09682 (2019) - [i5]Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi:
Binary Classification with Bounded Abstention Rate. CoRR abs/1905.09561 (2019) - [i4]Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi:
Active Learning for Binary Classification with Abstention. CoRR abs/1906.00303 (2019) - [i3]Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi:
Adaptive Sampling for Estimating Multiple Probability Distributions. CoRR abs/1910.12406 (2019) - 2018
- [j1]Shubhanshu Shekhar, Sebastien Roch, Siavash Mirarab:
Species Tree Estimation Using ASTRAL: How Many Genes Are Enough? IEEE ACM Trans. Comput. Biol. Bioinform. 15(5): 1738-1747 (2018) - 2017
- [c2]Shubhanshu Shekhar, Tara Javidi:
Bayesian function optimization with adaptive discretization. Allerton 2017: 533-540 - [c1]Shubhanshu Shekhar, Sebastien Roch, Siavash Mirarab:
Species Tree Estimation Using ASTRAL: How Many Genes Are Enough? RECOMB 2017: 393-395 - [i2]Shubhanshu Shekhar, Sebastien Roch, Siavash Mirarab:
Species tree estimation using ASTRAL: how many genes are enough? CoRR abs/1704.06831 (2017) - [i1]Shubhanshu Shekhar, Tara Javidi:
Gaussian Process bandits with adaptive discretization. CoRR abs/1712.01447 (2017)
Coauthor Index
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