Ramdas, Aaditya

76 publications

ICLR 2025 Conformalized Interactive Imitation Learning: Handling Expert Shift and Intermittent Feedback Michelle D Zhao, Henny Admoni, Reid Simmons, Aaditya Ramdas, Andrea Bajcsy

ICLRW 2025 Conformalized Interactive Imitation Learning: Handling Expert Shift and Intermittent Feedback Michelle D Zhao, Henny Admoni, Reid Simmons, Aaditya Ramdas, Andrea Bajcsy

ICML 2025 Improving the Statistical Efficiency of Cross-Conformal Prediction Matteo Gasparin, Aaditya Ramdas

AISTATS 2025 Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect Ojash Neopane, Aaditya Ramdas, Aarti Singh

TMLR 2025 Online Selective Conformal Inference: Errors and Solutions Yusuf Sale, Aaditya Ramdas

ICML 2025 Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect Ojash Neopane, Aaditya Ramdas, Aarti Singh

NeurIPS 2025 Private Evolution Converges Tomás González, Giulia Fanti, Aaditya Ramdas

ICLR 2025 QA-Calibration of Language Model Confidence Scores Putra Manggala, Atalanti A. Mastakouri, Elke Kirschbaum, Shiva Kasiviswanathan, Aaditya Ramdas

CLeaR 2025 Scalable Causal Structure Learning via Amortized Conditional Independence Testing James Leiner, Brian Manzo, Aaditya Ramdas, Wesley Tansey

AISTATS 2025 Sequential Kernelized Stein Discrepancy Diego Martinez-Taboada, Aaditya Ramdas

NeurIPS 2025 Sequentially Auditing Differential Privacy Tomás González, Mateo Dulce Rubio, Aaditya Ramdas, Mónica Ribero

NeurIPS 2025 Sharp Matrix Empirical Bernstein Inequalities Hongjian Wang, Aaditya Ramdas

TMLR 2025 Time-Uniform Confidence Spheres for Means of Random Vectors Ben Chugg, Hongjian Wang, Aaditya Ramdas

COLT 2025 Time-Uniform Self-Normalized Concentration for Vector-Valued Processes (Extended Abstract) Justin Whitehouse, Zhiwei Steven Wu, Aaditya Ramdas

NeurIPS 2024 Bias Detection via Signaling Yiling Chen, Tao Lin, Ariel D. Procaccia, Aaditya Ramdas, Itai Shapira

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

AISTATS 2024 Differentially Private Conditional Independence Testing Iden Kalemaj, Shiva Kasiviswanathan, Aaditya Ramdas

AISTATS 2024 Graph Fission and Cross-Validation James Leiner, Aaditya Ramdas

AISTATS 2024 Online Multiple Testing with E-Values Ziyu Xu, Aaditya Ramdas

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

CLeaR 2024 Semiparametric Efficient Inference in Adaptive Experiments Thomas Cook, Alan Mishler, Aaditya Ramdas

AISTATS 2024 Testing Exchangeability by Pairwise Betting Aytijhya Saha, Aaditya Ramdas

ICML 2024 Total Variation Floodgate for Variable Importance Inference in Classification Wenshuo Wang, Lucas Janson, Lihua Lei, Aaditya Ramdas

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

JMLR 2023 A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds Ben Chugg, Hongjian Wang, Aaditya Ramdas

NeurIPS 2023 Adaptive Privacy Composition for Accuracy-First Mechanisms Ryan M Rogers, Gennady Samorodnitsk, Steven Z. Wu, Aaditya Ramdas

NeurIPS 2023 An Efficient Doubly-Robust Test for the Kernel Treatment Effect Diego Martinez Taboada, Aaditya Ramdas, Edward Kennedy

NeurIPS 2023 Auditing Fairness by Betting Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas

NeurIPS 2023 Counterfactually Comparing Abstaining Classifiers Yo Joong Choe, Aditya Gangrade, Aaditya Ramdas

ICML 2023 Fully-Adaptive Composition in Differential Privacy Justin Whitehouse, Aaditya Ramdas, Ryan Rogers, Steven Wu

AISTATS 2023 Huber-Robust Confidence Sequences Hongjian Wang, Aaditya Ramdas

ICML 2023 Nonparametric Extensions of Randomized Response for Private Confidence Sets Ian Waudby-Smith, Steven Wu, Aaditya Ramdas

NeurIPS 2023 On the Sublinear Regret of GP-UCB Justin Whitehouse, Aaditya Ramdas, Steven Z. Wu

ICML 2023 Online Platt Scaling with Calibeating Chirag Gupta, Aaditya Ramdas

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

NeurIPSW 2023 Semiparametric Efficient Inference in Adaptive Experiments Thomas Cook, Alan Mishler, Aaditya Ramdas

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

ICML 2023 Sequential Kernelized Independence Testing Aleksandr Podkopaev, Patrick Blöbaum, Shiva Kasiviswanathan, Aaditya Ramdas

NeurIPS 2023 Sequential Predictive Two-Sample and Independence Testing Aleksandr Podkopaev, Aaditya Ramdas

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

NeurIPS 2022 Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints Justin Whitehouse, Aaditya Ramdas, Steven Z. Wu, Ryan M Rogers

COLT 2022 Faster Online Calibration Without Randomization: Interval Forecasts and the Power of Two Choices Chirag Gupta, Aaditya Ramdas

CLeaR 2022 Interactive Rank Testing by Betting Boyan Duan, Aaditya Ramdas, Larry Wasserman

ICLR 2022 Top-Label Calibration and Multiclass-to-Binary Reductions Chirag Gupta, Aaditya Ramdas

ICLR 2022 Tracking the Risk of a Deployed Model and Detecting Harmful Distribution Shifts Aleksandr Podkopaev, Aaditya Ramdas

NeurIPS 2021 A Unified Framework for Bandit Multiple Testing Ziyu Xu, Ruodu Wang, Aaditya Ramdas

JMLR 2021 Asynchronous Online Testing of Multiple Hypotheses Tijana Zrnic, Aaditya Ramdas, Michael I. Jordan

ICML 2021 Distribution-Free Calibration Guarantees for Histogram Binning Without Sample Splitting Chirag Gupta, Aaditya Ramdas

UAI 2021 Distribution-Free Uncertainty Quantification for Classification Under Label Shift Aleksandr Podkopaev, Aaditya Ramdas

ICML 2021 Off-Policy Confidence Sequences Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas

JMLR 2021 Path Length Bounds for Gradient Descent and Flow Chirag Gupta, Sivaraman Balakrishnan, Aaditya Ramdas

ALT 2021 Uncertainty Quantification Using Martingales for Misspecified Gaussian Processes Willie Neiswanger, Aaditya Ramdas

NeurIPS 2020 Confidence Sequences for Sampling Without Replacement Ian Waudby-Smith, Aaditya Ramdas

NeurIPS 2020 Distribution-Free Binary Classification: Prediction Sets, Confidence Intervals and Calibration Chirag Gupta, Aleksandr Podkopaev, Aaditya Ramdas

ICML 2020 Familywise Error Rate Control by Interactive Unmasking Boyan Duan, Aaditya Ramdas, Larry Wasserman

ICML 2020 On Conditional Versus Marginal Bias in Multi-Armed Bandits Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo

ICML 2020 Online Control of the False Coverage Rate and False Sign Rate Asaf Weinstein, Aaditya Ramdas

AISTATS 2020 The Power of Batching in Multiple Hypothesis Testing Tijana Zrnic, Daniel Jiang, Aaditya Ramdas, Michael Jordan

AISTATS 2019 A Higher-Order Kolmogorov-Smirnov Test Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Aaditya Ramdas, Ryan J. Tibshirani

NeurIPS 2019 ADDIS: An Adaptive Discarding Algorithm for Online FDR Control with Conservative Nulls Jinjin Tian, Aaditya Ramdas

NeurIPS 2019 Are Sample Means in Multi-Armed Bandits Positively or Negatively Biased? Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo

NeurIPS 2019 Conformal Prediction Under Covariate Shift Ryan J Tibshirani, Rina Foygel Barber, Emmanuel Candes, Aaditya Ramdas

ICML 2018 SAFFRON: An Adaptive Algorithm for Online Control of the False Discovery Rate Aaditya Ramdas, Tijana Zrnic, Martin Wainwright, Michael Jordan

NeurIPS 2017 A Framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control Fanny Yang, Aaditya Ramdas, Kevin G. Jamieson, Martin J. Wainwright

ICLR 2017 Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton

NeurIPS 2017 Online Control of the False Discovery Rate with Decaying Memory Aaditya Ramdas, Fanny Yang, Martin J. Wainwright, Michael I Jordan

UAI 2016 Sequential Nonparametric Testing with the Law of the Iterated Logarithm Akshay Balsubramani, Aaditya Ramdas

IJCAI 2015 Advances in Nonparametric Hypothesis Testing Aaditya Ramdas

NeurIPS 2015 Fast Two-Sample Testing with Analytic Representations of Probability Measures Kacper P Chwialkowski, Aaditya Ramdas, Dino Sejdinovic, Arthur Gretton

IJCAI 2015 Nonparametric Independence Testing for Small Sample Sizes Aaditya Ramdas, Leila Wehbe

AAAI 2015 On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions Aaditya Ramdas, Sashank Jakkam Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman

AISTATS 2015 On the High Dimensional Power of a Linear-Time Two Sample Test Under Mean-Shift Alternatives Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman

AISTATS 2014 An Analysis of Active Learning with Uniform Feature Noise Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman

ICML 2014 Margins, Kernels and Non-Linear Smoothed Perceptrons Aaditya Ramdas, Javier Peña

ALT 2013 Algorithmic Connections Between Active Learning and Stochastic Convex Optimization Aaditya Ramdas, Aarti Singh

ICML 2013 Optimal Rates for Stochastic Convex Optimization Under Tsybakov Noise Condition Aaditya Ramdas, Aarti Singh