Shubhanshu Shekhar

14 papers · 2019–2026 · 6 venues · across top CS/AI venues

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Achievements

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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (28)

💎 Century Club · Bronze 🔥 Unstoppable · Bronze 🗃️ Keyword Collector (77)

Venues

ICML (4) AISTATS (3) UAI (3) NeurIPS (2) JMLR (1) L4DC (1)

Top co-authors

Aaditya Ramdas (6) Tara Javidi (5) Mohammad Ghavamzadeh (3) Ilmun Kim (2) Mohammad Javad Khojasteh (1) Alessandro Lazaric (1) Shubhhi Singh (1) Patrick Forré (1) Teodora Pandeva (1) Zachary Lipton (1)

Research topics

Machine Learning (11) Optimization & Theory (8) Mathematics & Optimization (6) Learning Types (5) Mathematics (4) Artificial Intelligence (3) Optimization (3) Reinforcement Learning (2) Application Areas (2) Core AI (2) Core Methods (2) Statistics (2) Deep Learning (1) Robotics (1) Applications (1)

Keywords

gaussian process (4) confidence sequence (3) adaptive sampling (2) two-sample test (2) false alarm (2) regret bound (2) bayesian optimization (2) sequential estimation (2) detection delay (2) permutation test (2) adversarial robustness (1) fair classification (1) markov decision process (1) representation learning (1) active learning (1) sample complexity (1) gaussian process regression (1) uncertainty quantification (1) regret analysis (1) reproducing kernel hilbert space (1)

Papers

Learning-based Optimal Admission Control for Erlang-B Queuing Systems UAI 2026 Deep anytime-valid hypothesis testing AISTATS 2024 Reducing sequential change detection to sequential estimation ICML 2024 A Permutation-Free Kernel Independence Test JMLR 2023 Risk-limiting financial audits via weighted sampling without replacement UAI 2023 Sequential Changepoint Detection via Backward Confidence Sequences ICML 2023 A permutation-free kernel two-sample test NeurIPS 2022 Instance Dependent Regret Analysis of Kernelized Bandits ICML 2022 Adaptive Sampling for Minimax Fair Classification NeurIPS 2021 Significance of Gradient Information in Bayesian Optimization AISTATS 2021 Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric L4DC 2021 Active Model Estimation in Markov Decision Processes UAI 2020 Adaptive Sampling for Estimating Probability Distributions ICML 2020 Multiscale Gaussian Process Level Set Estimation AISTATS 2019