Aaditya Ramdas

According to our database1, Aaditya Ramdas authored at least 59 papers between 2012 and 2021.

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Bibliography

2021
Nonparametric Iterated-Logarithm Extensions of the Sequential Generalized Likelihood Ratio Test.
IEEE J. Sel. Areas Inf. Theory, 2021

Asynchronous Online Testing of Multiple Hypotheses.
J. Mach. Learn. Res., 2021

Top-label calibration.
CoRR, 2021

A unified framework for bandit multiple testing.
CoRR, 2021

Sequential Estimation of Convex Divergences using Reverse Submartingales and Exchangeable Filtrations.
CoRR, 2021

Distribution-free uncertainty quantification for classification under label shift.
CoRR, 2021

How can one test if a binary sequence is exchangeable? Fork-convex hulls, supermartingales, and Snell envelopes.
CoRR, 2021

Off-Policy Confidence Sequences.
Proceedings of the 38th International Conference on Machine Learning, 2021

Distribution-Free Calibration Guarantees for Histogram Binning without Sample Splitting.
Proceedings of the 38th International Conference on Machine Learning, 2021

Uncertainty quantification using martingales for misspecified Gaussian processes.
Proceedings of the Algorithmic Learning Theory, 2021

2020
Confidence sequences for sampling without replacement.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Distribution-free binary classification: prediction sets, confidence intervals and calibration.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Control of the False Coverage Rate and False Sign Rate.
Proceedings of the 37th International Conference on Machine Learning, 2020

On Conditional Versus Marginal Bias in Multi-Armed Bandits.
Proceedings of the 37th International Conference on Machine Learning, 2020

Familywise Error Rate Control by Interactive Unmasking.
Proceedings of the 37th International Conference on Machine Learning, 2020

Analyzing Student Strategies In Blended Courses Using Clickstream Data.
Proceedings of the 13th International Conference on Educational Data Mining, 2020

The Power of Batching in Multiple Hypothesis Testing.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Decoding From Pooled Data: Phase Transitions of Message Passing.
IEEE Trans. Inf. Theory, 2019

Decoding from Pooled Data: Sharp Information-Theoretic Bounds.
SIAM J. Math. Data Sci., 2019

Path Length Bounds for Gradient Descent and Flow.
CoRR, 2019

On the bias, risk and consistency of sample means in multi-armed bandits.
CoRR, 2019

Conformal Prediction Under Covariate Shift.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

ADDIS: an adaptive discarding algorithm for online FDR control with conservative nulls.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Are sample means in multi-armed bandits positively or negatively biased?
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Foundations of Large-Scale Sequential Experimentation.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

A Higher-Order Kolmogorov-Smirnov Test.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Iterative Methods for Solving Factorized Linear Systems.
SIAM J. Matrix Anal. Appl., 2018

SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Rows versus Columns: Randomized Kaczmarz or Gauss-Seidel for Ridge Regression.
SIAM J. Sci. Comput., 2017

On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests.
Entropy, 2017

DAGGER: A sequential algorithm for FDR control on DAGs.
CoRR, 2017

A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Online control of the false discovery rate with decaying memory.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy.
Proceedings of the 5th International Conference on Learning Representations, 2017

QuTE: Decentralized multiple testing on sensor networks with false discovery rate control.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2016
Towards a deeper geometric, analytic and algorithmic understanding of margins.
Optim. Methods Softw., 2016

Classification Accuracy as a Proxy for Two Sample Testing.
CoRR, 2016

Function-Specific Mixing Times and Concentration Away from Equilibrium.
CoRR, 2016

Universality of Mallows' and degeneracy of Kendall's kernels for rankings.
CoRR, 2016

Asymptotic behavior of ℓ<sub>p</sub>-based Laplacian regularization in semi-supervised learning.
CoRR, 2016

Sequential Nonparametric Testing with the Law of the Iterated Logarithm.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Minimax lower bounds for linear independence testing.
Proceedings of the IEEE International Symposium on Information Theory, 2016

2015
Convergence Properties of the Randomized Extended Gauss-Seidel and Kaczmarz Methods.
SIAM J. Matrix Anal. Appl., 2015

Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing.
CoRR, 2015

Fast Two-Sample Testing with Analytic Representations of Probability Measures.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Nonparametric Independence Testing for Small Sample Sizes.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Advances in Nonparametric Hypothesis Testing.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Kernel MMD, the Median Heuristic and Distance Correlation in High Dimensions.
CoRR, 2014

Fast and Flexible ADMM Algorithms for Trend Filtering.
CoRR, 2014

On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives.
CoRR, 2014

Rows vs Columns for Linear Systems of Equations - Randomized Kaczmarz or Coordinate Descent?
CoRR, 2014

Margins, Kernels and Non-linear Smoothed Perceptrons.
Proceedings of the 31th International Conference on Machine Learning, 2014

An Analysis of Active Learning with Uniform Feature Noise.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Optimal rates for stochastic convex optimization under Tsybakov noise condition.
Proceedings of the 30th International Conference on Machine Learning, 2013

Exploring the intersection of active learning and stochastic convex optimization.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Algorithmic Connections between Active Learning and Stochastic Convex Optimization.
Proceedings of the Algorithmic Learning Theory - 24th International Conference, 2013

2012
Optimal Stochastic Convex Optimization Through The Lens Of Active Learning
CoRR, 2012


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