Aaditya Ramdas

195 papers A* 41A 15B 5Journal 119Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A complete characterization of testable hypotheses. CoRR Martin Larsson, Johannes Ruf, Aaditya Ramdas
2026	J	`jnl`	Huber-Robust Likelihood Ratio Tests for Composite Nulls and Alternatives. IEEE Trans. Inf. Theory Aytijhya Saha, Aaditya Ramdas
2026	J	`jnl`	Improving Wald's (Approximate) Sequential Probability Ratio Test by Avoiding Overshoot. IEEE Trans. Inf. Theory Lasse Fischer, Aaditya Ramdas
2026	J	`jnl`	On admissibility in post-hoc hypothesis testing. Int. J. Approx. Reason. Ben Chugg, Tyron Lardy, Aaditya Ramdas, Peter Grünwald
2026	J	`jnl`	Online monotone density estimation and log-optimal calibration. CoRR Rohan Hore, Ruodu Wang, Aaditya Ramdas
2026	J	`jnl`	Operationalizing Stein's Method for Online Linear Optimization: CLT-Based Optimal Tradeoffs. CoRR Zhiyu Zhang, Aaditya Ramdas
2026	J	`jnl`	Tighter Confidence Intervals under Without Replacement Sampling via Empirical Rate Functions. CoRR Shubhanshu Shekhar, Aaditya Ramdas
2026	J	`jnl`	Universal Sequential Changepoint Detection of Quantum Observables via Classical Shadows. CoRR Matteo Zecchin, Osvaldo Simeone, Aaditya Ramdas
2025	A*	`conf`	Conformalized Interactive Imitation Learning: Handling Expert Shift and Intermittent Feedback. ICLR Michelle D. Zhao, Henny Admoni, Reid G. Simmons, Aaditya Ramdas, Andrea Bajcsy
2025	J	`jnl`	Corrections to "Nonparametric Two-Sample Testing by Betting". IEEE Trans. Inf. Theory Shubhanshu Shekhar, Aaditya Ramdas
2025	J	`jnl`	Eventually LIL Regret: Almost Sure ln ln T Regret for a sub-Gaussian Mixture on Unbounded Data. CoRR Shubhada Agrawal, Aaditya Ramdas
2025	J	`jnl`	Gradient flow for deep equilibrium single-index models. CoRR Sanjit Dandapanthula, Aaditya Ramdas
2025	A*	`conf`	Improving the Statistical Efficiency of Cross-Conformal Prediction. ICML Matteo Gasparin, Aaditya Ramdas
2025	J	`jnl`	Improving the statistical efficiency of cross-conformal prediction. CoRR Matteo Gasparin, Aaditya Ramdas
2025	A	`conf`	Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect. AISTATS Ojash Neopane, Aaditya Ramdas, Aarti Singh
2025	J	`jnl`	On Stopping Times of Power-one Sequential Tests: Tight Lower and Upper Bounds. CoRR Shubhada Agrawal, Aaditya Ramdas
2025	J	`jnl`	Online Selective Conformal Inference: Errors and Solutions. Trans. Mach. Learn. Res. Yusuf Sale, Aaditya Ramdas
2025	J	`jnl`	Online Selective Conformal Prediction: Errors and Solutions. CoRR Yusuf Sale, Aaditya Ramdas
2025	J	`jnl`	Optimal Transportation and Alignment Between Gaussian Measures. CoRR Sanjit Dandapanthula, Aleksandr Podkopaev, Shiva Prasad Kasiviswanathan, Aaditya Ramdas, Ziv Goldfeld
2025	A*	`conf`	Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect. ICML Ojash Neopane, Aaditya Ramdas, Aarti Singh
2025	J	`jnl`	Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect. CoRR Ojash Neopane, Aaditya Ramdas, Aarti Singh
2025	J	`jnl`	Post-detection inference for sequential changepoint localization. CoRR Aytijhya Saha, Aaditya Ramdas
2025	J	`jnl`	Private Evolution Converges. CoRR Tomás González, Giulia Fanti, Aaditya Ramdas
2025	A*	`conf`	QA-Calibration of Language Model Confidence Scores. ICLR Putra Manggala, Atalanti-Anastasia Mastakouri, Elke Kirschbaum, Shiva Prasad Kasiviswanathan, Aaditya Ramdas
2025	J	`jnl`	Quantum Sequential Universal Hypothesis Testing. CoRR Matteo Zecchin, Osvaldo Simeone, Aaditya Ramdas
2025	—	`conf`	Scalable Causal Structure Learning via Amortized Conditional Independence Testing. CLeaR James Leiner, Brian Manzo, Aaditya Ramdas, Wesley Tansey
2025	A	`conf`	Sequential Kernelized Stein Discrepancy. AISTATS Diego Martinez-Taboada, Aaditya Ramdas
2025	J	`jnl`	Sequentially Auditing Differential Privacy. CoRR Tomás González, Mateo Dulce-Rubio, Aaditya Ramdas, Mónica Ribero
2025	J	`jnl`	Time-Uniform Confidence Spheres for Means of Random Vectors. Trans. Mach. Learn. Res. Ben Chugg, Hongjian Wang, Aaditya Ramdas
2025	A*	`conf`	Time-Uniform Self-Normalized Concentration for Vector-Valued Processes (Extended Abstract). COLT Justin Whitehouse, Zhiwei Steven Wu, Aaditya Ramdas
2025	J	`jnl`	Universal Inference Meets Random Projections: A Scalable Test for Log-Concavity. J. Comput. Graph. Stat. Robin Dunn, Aditya Gangrade, Larry A. Wasserman, Aaditya Ramdas
2025	J	`jnl`	Vector-valued self-normalized concentration inequalities beyond sub-Gaussianity. CoRR Diego Martinez-Taboada, Tomás González, Aaditya Ramdas
2024	J	`jnl`	Bias Detection Via Signaling. CoRR Yiling Chen, Tao Lin, Ariel D. Procaccia, Aaditya Ramdas, Itai Shapira
2024	A*	`conf`	Bias Detection via Signaling. NeurIPS Yiling Chen, Tao Lin, Ariel D. Procaccia, Aaditya Ramdas, Itai Shapira
2024	J	`jnl`	Combining Evidence Across Filtrations. CoRR Yo Joong Choe, Aaditya Ramdas
2024	J	`jnl`	Comparing Sequential Forecasters. Oper. Res. Yo Joong Choe, Aaditya Ramdas
2024	J	`jnl`	Conformal online model aggregation. CoRR Matteo Gasparin, Aaditya Ramdas
2024	J	`jnl`	Conformalized Interactive Imitation Learning: Handling Expert Shift and Intermittent Feedback. CoRR Michelle Zhao, Reid G. Simmons, Henny Admoni, Aaditya Ramdas, Andrea Bajcsy
2024	A	`conf`	Deep anytime-valid hypothesis testing. AISTATS Teodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar
2024	A	`conf`	Differentially Private Conditional Independence Testing. AISTATS Iden Kalemaj, Shiva Prasad Kasiviswanathan, Aaditya Ramdas
2024	A	`conf`	Graph fission and cross-validation. AISTATS James Leiner, Aaditya Ramdas
2024	J	`jnl`	Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect. CoRR Ojash Neopane, Aaditya Ramdas, Aarti Singh
2024	J	`jnl`	Nonparametric Two-Sample Testing by Betting. IEEE Trans. Inf. Theory Shubhanshu Shekhar, Aaditya Ramdas
2024	A	`conf`	Online multiple testing with e-values. AISTATS Ziyu Xu, Aaditya Ramdas
2024	A*	`conf`	Reducing sequential change detection to sequential estimation. ICML Shubhanshu Shekhar, Aaditya Ramdas
2024	—	`conf`	Semiparametric Efficient Inference in Adaptive Experiments. CLeaR Thomas Cook, Alan Mishler, Aaditya Ramdas
2024	J	`jnl`	Sequential Kernelized Stein Discrepancy. CoRR Diego Martinez-Taboada, Aaditya Ramdas
2024	A	`conf`	Testing exchangeability by pairwise betting. AISTATS Aytijhya Saha, Aaditya Ramdas
2024	A*	`conf`	Total Variation Floodgate for Variable Importance Inference in Classification. ICML Wenshuo Wang, Lucas Janson, Lihua Lei, Aaditya Ramdas
2024	J	`jnl`	β-calibration of Language Model Confidence Scores for Generative QA. CoRR Putra Manggala, Atalanti-Anastasia Mastakouri, Elke Kirschbaum, Shiva Prasad Kasiviswanathan, Aaditya Ramdas
2023	J	`jnl`	A Permutation-Free Kernel Independence Test. J. Mach. Learn. Res. Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas
2023	J	`jnl`	A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds. J. Mach. Learn. Res. Ben Chugg, Hongjian Wang, Aaditya Ramdas
2023	J	`jnl`	A unified recipe for deriving (time-uniform) PAC-Bayes bounds. CoRR Ben Chugg, Hongjian Wang, Aaditya Ramdas
2023	A*	`conf`	Adaptive Privacy Composition for Accuracy-first Mechanisms. NeurIPS Ryan M. Rogers, Gennady Samorodnitsky, Zhiwei Steven Wu, Aaditya Ramdas
2023	J	`jnl`	Adaptive Privacy Composition for Accuracy-first Mechanisms. CoRR Ryan Rogers, Gennady Samorodnitsky, Zhiwei Steven Wu, Aaditya Ramdas
2023	A*	`conf`	An Efficient Doubly-Robust Test for the Kernel Treatment Effect. NeurIPS Diego Martinez-Taboada, Aaditya Ramdas, Edward Kennedy
2023	—	`conf`	Anytime-Valid Confidence Sequences in an Enterprise A/B Testing Platform. WWW (Companion Volume) Akash Maharaj, Ritwik Sinha, David Arbour, Ian Waudby-Smith, Simon Z. Liu, Moumita Sinha, Raghavendra Addanki, Aaditya Ramdas, Manas Garg, Viswanathan Swaminathan
2023	J	`jnl`	Anytime-valid t-tests and confidence sequences for Gaussian means with unknown variance. CoRR Hongjian Wang, Aaditya Ramdas
2023	A*	`conf`	Auditing Fairness by Betting. NeurIPS Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas
2023	J	`jnl`	Auditing Fairness by Betting. CoRR Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas
2023	A*	`conf`	Counterfactually Comparing Abstaining Classifiers. NeurIPS Yo Joong Choe, Aditya Gangrade, Aaditya Ramdas
2023	J	`jnl`	Counterfactually Comparing Abstaining Classifiers. CoRR Yo Joong Choe, Aditya Gangrade, Aaditya Ramdas
2023	J	`jnl`	Deep anytime-valid hypothesis testing. CoRR Teodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar
2023	J	`jnl`	Differentially Private Conditional Independence Testing. CoRR Iden Kalemaj, Shiva Prasad Kasiviswanathan, Aaditya Ramdas
2023	A*	`conf`	Fully-Adaptive Composition in Differential Privacy. ICML Justin Whitehouse, Aaditya Ramdas, Ryan Rogers, Steven Wu
2023	J	`jnl`	Huber-Robust Confidence Sequences. CoRR Hongjian Wang, Aaditya Ramdas
2023	A	`conf`	Huber-robust confidence sequences. AISTATS Hongjian Wang, Aaditya Ramdas
2023	J	`jnl`	Improved Self-Normalized Concentration in Hilbert Spaces: Sublinear Regret for GP-UCB. CoRR Justin Whitehouse, Zhiwei Steven Wu, Aaditya Ramdas
2023	J	`jnl`	Martingale Methods for Sequential Estimation of Convex Functionals and Divergences. IEEE Trans. Inf. Theory Tudor Manole, Aaditya Ramdas
2023	A*	`conf`	Nonparametric Extensions of Randomized Response for Private Confidence Sets. ICML Ian Waudby-Smith, Zhiwei Steven Wu, Aaditya Ramdas
2023	A*	`conf`	On the Sublinear Regret of GP-UCB. NeurIPS Justin Whitehouse, Aaditya Ramdas, Zhiwei Steven Wu
2023	J	`jnl`	On the near-optimality of betting confidence sets for bounded means. CoRR Shubhanshu Shekhar, Aaditya Ramdas
2023	A*	`conf`	Online Platt Scaling with Calibeating. ICML Chirag Gupta, Aaditya Ramdas
2023	J	`jnl`	Online Platt Scaling with Calibeating. CoRR Chirag Gupta, Aaditya Ramdas
2023	J	`jnl`	Randomized and Exchangeable Improvements of Markov's, Chebyshev's and Chernoff's Inequalities. CoRR Aaditya Ramdas, Tudor Manole
2023	J	`jnl`	Reducing sequential change detection to sequential estimation. CoRR Shubhanshu Shekhar, Aaditya Ramdas
2023	J	`jnl`	Risk-limiting Financial Audits via Weighted Sampling without Replacement. CoRR Shubhanshu Shekhar, Ziyu Xu, Zachary C. Lipton, Pierre J. Liang, Aaditya Ramdas
2023	A	`conf`	Risk-limiting financial audits via weighted sampling without replacement. UAI Shubhanshu Shekhar, Ziyu Xu, Zachary C. Lipton, Pierre J. Liang, Aaditya Ramdas
2023	J	`jnl`	Semiparametric Efficient Inference in Adaptive Experiments. CoRR Thomas Cook, Alan Mishler, Aaditya Ramdas
2023	A*	`conf`	Sequential Changepoint Detection via Backward Confidence Sequences. ICML Shubhanshu Shekhar, Aaditya Ramdas
2023	A*	`conf`	Sequential Kernelized Independence Testing. ICML Aleksandr Podkopaev, Patrick Blöbaum, Shiva Prasad Kasiviswanathan, Aaditya Ramdas
2023	A*	`conf`	Sequential Predictive Two-Sample and Independence Testing. NeurIPS Aleksandr Podkopaev, Aaditya Ramdas
2023	J	`jnl`	Sequential Predictive Two-Sample and Independence Testing. CoRR Aleksandr Podkopaev, Aaditya Ramdas
2023	J	`jnl`	Sequential change detection via backward confidence sequences. CoRR Shubhanshu Shekhar, Aaditya Ramdas
2023	J	`jnl`	Time-Uniform Confidence Spheres for Means of Random Vectors. CoRR Ben Chugg, Hongjian Wang, Aaditya Ramdas
2023	J	`jnl`	When do exact and powerful p-values and e-values exist? CoRR Zhenyuan Zhang, Aaditya Ramdas, Ruodu Wang
2022	J	`jnl`	A Permutation-Free Kernel Independence Test. CoRR Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas
2022	J	`jnl`	A Permutation-free Kernel Two-Sample Test. CoRR Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas
2022	J	`jnl`	A composite generalization of Ville's martingale theorem. CoRR Johannes Ruf, Martin Larsson, Wouter M. Koolen, Aaditya Ramdas
2022	A*	`conf`	A permutation-free kernel two-sample test. NeurIPS Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas
2022	J	`jnl`	Anytime-valid off-policy inference for contextual bandits. CoRR Ian Waudby-Smith, Lili Wu, Aaditya Ramdas, Nikos Karampatziakis, Paul Mineiro
2022	A*	`conf`	Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints. NeurIPS Justin Whitehouse, Aaditya Ramdas, Zhiwei Steven Wu, Ryan M. Rogers
2022	J	`jnl`	Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints. CoRR Justin Whitehouse, Zhiwei Steven Wu, Aaditya Ramdas, Ryan Rogers
2022	A*	`conf`	Faster online calibration without randomization: interval forecasts and the power of two choices. COLT Chirag Gupta, Aaditya Ramdas
2022	J	`jnl`	Faster online calibration without randomization: interval forecasts and the power of two choices. CoRR Chirag Gupta, Aaditya Ramdas
2022	J	`jnl`	Fully Adaptive Composition in Differential Privacy. CoRR Justin Whitehouse, Aaditya Ramdas, Ryan Rogers, Zhiwei Steven Wu
2022	J	`jnl`	Game-theoretic statistics and safe anytime-valid inference. CoRR Aaditya Ramdas, Peter Grünwald, Vladimir Vovk, Glenn Shafer
2022	—	`conf`	Interactive rank testing by betting. CLeaR Boyan Duan, Aaditya Ramdas, Larry A. Wasserman
2022	J	`jnl`	Locally private nonparametric confidence intervals and sequences. CoRR Ian Waudby-Smith, Zhiwei Steven Wu, Aaditya Ramdas
2022	J	`jnl`	Nested conformal prediction and quantile out-of-bag ensemble methods. Pattern Recognit. Chirag Gupta, Arun K. Kuchibhotla, Aaditya Ramdas
2022	J	`jnl`	QuTE: decentralized multiple testing on sensor networks with false discovery rate control. CoRR Aaditya Ramdas, Jianbo Chen, Martin J. Wainwright, Michael I. Jordan
2022	J	`jnl`	Sequential Kernelized Independence Testing. CoRR Aleksandr Podkopaev, Patrick Blöbaum, Shiva Prasad Kasiviswanathan, Aaditya Ramdas
2022	J	`jnl`	Testing exchangeability: Fork-convexity, supermartingales and e-processes. Int. J. Approx. Reason. Aaditya Ramdas, Johannes Ruf, Martin Larsson, Wouter M. Koolen
2022	A*	`conf`	Top-label calibration and multiclass-to-binary reductions. ICLR Chirag Gupta, Aaditya Ramdas
2022	A*	`conf`	Tracking the risk of a deployed model and detecting harmful distribution shifts. ICLR Aleksandr Podkopaev, Aaditya Ramdas
2021	A*	`conf`	A unified framework for bandit multiple testing. NeurIPS Ziyu Xu, Ruodu Wang, Aaditya Ramdas
2021	J	`jnl`	A unified framework for bandit multiple testing. CoRR Ziyu Xu, Ruodu Wang, Aaditya Ramdas
2021	J	`jnl`	Asynchronous Online Testing of Multiple Hypotheses. J. Mach. Learn. Res. Tijana Zrnic, Aaditya Ramdas, Michael I. Jordan
2021	—	`conf`	Best Arm Identification under Additive Transfer Bandits. ACSCC Ojash Neopane, Aaditya Ramdas, Aarti Singh
2021	J	`jnl`	Best Arm Identification under Additive Transfer Bandits. CoRR Ojash Neopane, Aaditya Ramdas, Aarti Singh
2021	J	`jnl`	Comparing Sequential Forecasters. CoRR Yo Joong Choe, Aaditya Ramdas
2021	A*	`conf`	Distribution-Free Calibration Guarantees for Histogram Binning without Sample Splitting. ICML Chirag Gupta, Aaditya Ramdas
2021	A	`conf`	Distribution-free uncertainty quantification for classification under label shift. UAI Aleksandr Podkopaev, Aaditya Ramdas
2021	J	`jnl`	Distribution-free uncertainty quantification for classification under label shift. CoRR Aleksandr Podkopaev, Aaditya Ramdas
2021	—	`conf`	Dynamic Algorithms for Online Multiple Testing. MSML Ziyu Xu, Aaditya Ramdas
2021	J	`jnl`	Game-theoretic Formulations of Sequential Nonparametric One- and Two-Sample Tests. CoRR Shubhanshu Shekhar, Aaditya Ramdas
2021	J	`jnl`	How can one test if a binary sequence is exchangeable? Fork-convex hulls, supermartingales, and Snell envelopes. CoRR Aaditya Ramdas, Johannes Ruf, Martin Larsson, Wouter M. Koolen
2021	J	`jnl`	Nonparametric Iterated-Logarithm Extensions of the Sequential Generalized Likelihood Ratio Test. IEEE J. Sel. Areas Inf. Theory Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo
2021	A*	`conf`	Off-Policy Confidence Sequences. ICML Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
2021	J	`jnl`	Off-policy Confidence Sequences. CoRR Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
2021	J	`jnl`	On the Bias, Risk, and Consistency of Sample Means in Multi-armed Bandits. SIAM J. Math. Data Sci. Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo
2021	J	`jnl`	Path Length Bounds for Gradient Descent and Flow. J. Mach. Learn. Res. Chirag Gupta, Sivaraman Balakrishnan, Aaditya Ramdas
2021	—	`conf`	RiLACS: Risk Limiting Audits via Confidence Sequences. E-VOTE-ID Ian Waudby-Smith, Philip B. Stark, Aaditya Ramdas
2021	J	`jnl`	Sequential Estimation of Convex Divergences using Reverse Submartingales and Exchangeable Filtrations. CoRR Tudor Manole, Aaditya Ramdas
2021	J	`jnl`	Tracking the risk of a deployed model and detecting harmful distribution shifts. CoRR Aleksandr Podkopaev, Aaditya Ramdas
2021	B	`conf`	Uncertainty quantification using martingales for misspecified Gaussian processes. ALT Willie Neiswanger, Aaditya Ramdas
2021	J	`jnl`	Universal Inference Meets Random Projections: A Scalable Test for Log-concavity. CoRR Robin Dunn, Larry A. Wasserman, Aaditya Ramdas
2020	B	`conf`	Analyzing Student Strategies In Blended Courses Using Clickstream Data. EDM Nil-Jana Akpinar, Aaditya Ramdas, Umut A. Acar
2020	J	`jnl`	Analyzing Student Strategies In Blended Courses Using Clickstream Data. CoRR Nil-Jana Akpinar, Aaditya Ramdas, Umut A. Acar
2020	A*	`conf`	Confidence sequences for sampling without replacement. NeurIPS Ian Waudby-Smith, Aaditya Ramdas
2020	A*	`conf`	Distribution-free binary classification: prediction sets, confidence intervals and calibration. NeurIPS Chirag Gupta, Aleksandr Podkopaev, Aaditya Ramdas
2020	J	`jnl`	Distribution-free binary classification: prediction sets, confidence intervals and calibration. CoRR Chirag Gupta, Aleksandr Podkopaev, Aaditya Ramdas
2020	A*	`conf`	Familywise Error Rate Control by Interactive Unmasking. ICML Boyan Duan, Aaditya Ramdas, Larry A. Wasserman
2020	A*	`conf`	On Conditional Versus Marginal Bias in Multi-Armed Bandits. ICML Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo
2020	A*	`conf`	Online Control of the False Coverage Rate and False Sign Rate. ICML Asaf Weinstein, Aaditya Ramdas
2020	A	`conf`	The Power of Batching in Multiple Hypothesis Testing. AISTATS Tijana Zrnic, Daniel L. Jiang, Aaditya Ramdas, Michael I. Jordan
2020	J	`jnl`	Uncertainty quantification using martingales for misspecified Gaussian processes. CoRR Willie Neiswanger, Aaditya Ramdas
2019	A	`conf`	A Higher-Order Kolmogorov-Smirnov Test. AISTATS Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Aaditya Ramdas, Ryan J. Tibshirani
2019	J	`jnl`	A Higher-Order Kolmogorov-Smirnov Test. CoRR Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Aaditya Ramdas, Ryan J. Tibshirani
2019	A*	`conf`	ADDIS: an adaptive discarding algorithm for online FDR control with conservative nulls. NeurIPS Jinjin Tian, Aaditya Ramdas
2019	A*	`conf`	Are sample means in multi-armed bandits positively or negatively biased? NeurIPS Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo
2019	A*	`conf`	Conformal Prediction Under Covariate Shift. NeurIPS Ryan J. Tibshirani, Rina Foygel Barber, Emmanuel J. Candès, Aaditya Ramdas
2019	J	`jnl`	Decoding From Pooled Data: Phase Transitions of Message Passing. IEEE Trans. Inf. Theory Ahmed El Alaoui, Aaditya Ramdas, Florent Krzakala, Lenka Zdeborová, Michael I. Jordan
2019	J	`jnl`	Decoding from Pooled Data: Sharp Information-Theoretic Bounds. SIAM J. Math. Data Sci. Ahmed El Alaoui, Aaditya Ramdas, Florent Krzakala, Lenka Zdeborová, Michael I. Jordan
2019	A*	`conf`	Foundations of Large-Scale Sequential Experimentation. KDD Aaditya Ramdas
2019	J	`jnl`	On the bias, risk and consistency of sample means in multi-armed bandits. CoRR Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo
2019	J	`jnl`	Path Length Bounds for Gradient Descent and Flow. CoRR Chirag Gupta, Sivaraman Balakrishnan, Aaditya Ramdas
2018	J	`jnl`	Asynchronous Online Testing of Multiple Hypotheses. CoRR Tijana Zrnic, Aaditya Ramdas, Michael I. Jordan
2018	J	`jnl`	Iterative Methods for Solving Factorized Linear Systems. SIAM J. Matrix Anal. Appl. Anna Ma, Deanna Needell, Aaditya Ramdas
2018	A*	`conf`	SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate. ICML Aaditya Ramdas, Tijana Zrnic, Martin J. Wainwright, Michael I. Jordan
2018	J	`jnl`	SAFFRON: an adaptive algorithm for online control of the false discovery rate. CoRR Aaditya Ramdas, Tijana Zrnic, Martin J. Wainwright, Michael I. Jordan
2017	—	`conf`	A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control. NIPS Fanny Yang, Aaditya Ramdas, Kevin Jamieson, Martin J. Wainwright
2017	J	`jnl`	A framework for Multi-A(rmed)/B(andit) testing with online FDR control. CoRR Fanny Yang, Aaditya Ramdas, Kevin Jamieson, Martin J. Wainwright
2017	J	`jnl`	DAGGER: A sequential algorithm for FDR control on DAGs. CoRR Aaditya Ramdas, Jianbo Chen, Martin J. Wainwright, Michael I. Jordan
2017	J	`jnl`	Decoding from Pooled Data: Phase Transitions of Message Passing. CoRR Ahmed El Alaoui, Aaditya Ramdas, Florent Krzakala, Lenka Zdeborová, Michael I. Jordan
2017	B	`conf`	Decoding from pooled data: Phase transitions of message passing. ISIT Ahmed El Alaoui, Aaditya Ramdas, Florent Krzakala, Lenka Zdeborová, Michael I. Jordan
2017	—	`conf`	Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy. ICLR (Poster) Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton
2017	J	`jnl`	On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests. Entropy Aaditya Ramdas, Nicolás García Trillos, Marco Cuturi
2017	—	`conf`	Online control of the false discovery rate with decaying memory. NIPS Aaditya Ramdas, Fanny Yang, Martin J. Wainwright, Michael I. Jordan
2017	J	`jnl`	Online control of the false discovery rate with decaying memory. CoRR Aaditya Ramdas, Fanny Yang, Martin J. Wainwright, Michael I. Jordan
2017	—	`conf`	QuTE: Decentralized multiple testing on sensor networks with false discovery rate control. CDC Aaditya Ramdas, Jianbo Chen, Martin J. Wainwright, Michael I. Jordan
2017	J	`jnl`	Rows versus Columns: Randomized Kaczmarz or Gauss-Seidel for Ridge Regression. SIAM J. Sci. Comput. Ahmed Hefny, Deanna Needell, Aaditya Ramdas
2016	J	`jnl`	Asymptotic behavior of ℓ CoRR Ahmed El Alaoui, Xiang Cheng, Aaditya Ramdas, Martin J. Wainwright, Michael I. Jordan
2016	J	`jnl`	Classification Accuracy as a Proxy for Two Sample Testing. CoRR Aaditya Ramdas, Aarti Singh, Larry A. Wasserman
2016	J	`jnl`	Decoding from Pooled Data: Sharp Information-Theoretic Bounds. CoRR Ahmed El Alaoui, Aaditya Ramdas, Florent Krzakala, Lenka Zdeborová, Michael I. Jordan
2016	J	`jnl`	Function-Specific Mixing Times and Concentration Away from Equilibrium. CoRR Maxim Rabinovich, Aaditya Ramdas, Michael I. Jordan, Martin J. Wainwright
2016	J	`jnl`	Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy. CoRR Danica J. Sutherland, Hsiao-Yu Fish Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton
2016	J	`jnl`	Minimax Lower Bounds for Linear Independence Testing. CoRR Aaditya Ramdas, David Isenberg, Aarti Singh, Larry A. Wasserman
2016	B	`conf`	Minimax lower bounds for linear independence testing. ISIT Aaditya Ramdas, David Isenberg, Aarti Singh, Larry A. Wasserman
2016	A	`conf`	Sequential Nonparametric Testing with the Law of the Iterated Logarithm. UAI Akshay Balsubramani, Aaditya Ramdas
2016	J	`jnl`	Towards a deeper geometric, analytic and algorithmic understanding of margins. Optim. Methods Softw. Aaditya Ramdas, Javier Peña
2016	J	`jnl`	Universality of Mallows' and degeneracy of Kendall's kernels for rankings. CoRR Horia Mania, Aaditya Ramdas, Martin J. Wainwright, Michael I. Jordan, Benjamin Recht
2015	J	`jnl`	Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing. CoRR Aaditya Ramdas, Sashank J. Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	A*	`conf`	Advances in Nonparametric Hypothesis Testing. IJCAI Aaditya Ramdas
2015	J	`jnl`	Algorithmic Connections Between Active Learning and Stochastic Convex Optimization. CoRR Aaditya Ramdas, Aarti Singh
2015	J	`jnl`	An Analysis of Active Learning With Uniform Feature Noise. CoRR Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	—	`—`	Computational and Statistical Advances in Testing and Learning. Aaditya Ramdas
2015	J	`jnl`	Convergence Properties of the Randomized Extended Gauss-Seidel and Kaczmarz Methods. SIAM J. Matrix Anal. Appl. Anna Ma, Deanna Needell, Aaditya Ramdas
2015	—	`conf`	Fast Two-Sample Testing with Analytic Representations of Probability Measures. NIPS Kacper Chwialkowski, Aaditya Ramdas, Dino Sejdinovic, Arthur Gretton
2015	J	`jnl`	Margins, Kernels and Non-linear Smoothed Perceptrons. CoRR Aaditya Ramdas, Javier Peña
2015	A*	`conf`	Nonparametric Independence Testing for Small Sample Sizes. IJCAI Aaditya Ramdas, Leila Wehbe
2015	A*	`conf`	On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions. AAAI Aaditya Ramdas, Sashank Jakkam Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	A	`conf`	On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives. AISTATS Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	J	`jnl`	Sequential Nonparametric Testing with the Law of the Iterated Logarithm. CoRR Aaditya Ramdas, Akshay Balsubramani
2014	A	`conf`	An Analysis of Active Learning with Uniform Feature Noise. AISTATS Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2014	J	`jnl`	Fast and Flexible ADMM Algorithms for Trend Filtering. CoRR Aaditya Ramdas, Ryan J. Tibshirani
2014	J	`jnl`	Kernel MMD, the Median Heuristic and Distance Correlation in High Dimensions. CoRR Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2014	A*	`conf`	Margins, Kernels and Non-linear Smoothed Perceptrons. ICML Aaditya Ramdas, Javier Peña
2014	J	`jnl`	On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives. CoRR Aaditya Ramdas, Sashank J. Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2014	J	`jnl`	Rows vs Columns for Linear Systems of Equations - Randomized Kaczmarz or Coordinate Descent? CoRR Aaditya Ramdas
2014	J	`jnl`	Towards A Deeper Geometric, Analytic and Algorithmic Understanding of Margins. CoRR Aaditya Ramdas, Javier Peña
2013	B	`conf`	Algorithmic Connections between Active Learning and Stochastic Convex Optimization. ALT Aaditya Ramdas, Aarti Singh
2013	—	`conf`	Exploring the intersection of active learning and stochastic convex optimization. GlobalSIP Aaditya Ramdas, Aarti Singh
2013	—	`conf`	Optimal rates for stochastic convex optimization under Tsybakov noise condition. ICML (1) Aaditya Ramdas, Aarti Singh
2012	J	`jnl`	Optimal Stochastic Convex Optimization Through The Lens Of Active Learning CoRR Aaditya Ramdas, Aarti Singh