Aaditya Ramdas – Publications

Safe, anytime-valid inference: confidence sequences, p-values/e-values, and e-processes (package) (tutorial)

• Game-theoretic statistics and safe anytime-valid inference
  A. Ramdas, P. Grunwald, V. Vovk, G. Shafer       arxiv

• Anytime-valid off-policy inference for contextual bandits
  I. Waudby-Smith, L. Wu, A. Ramdas, N. Karampatziakis, P. Mineiro       arxiv

• A composite generalization of Ville's martingale theorem
  J. Ruf, M. Larsson, W. Koolen, A. Ramdas       arxiv

• Catoni-style confidence sequences for heavy-tailed mean estimation
  H. Wang, A. Ramdas       arxiv  

• Nonparametric two-sample testing by betting
  S. Shekhar, A. Ramdas       arxiv  

• E-detectors: a nonparametric framework for online changepoint detection
  J. Shin, A. Ramdas, A. Rinaldo       arxiv  

• Comparing sequential forecasters
  Y.J. Choe, A. Ramdas       arxiv  

• Sequential estimation of convex functionals and divergences
  T. Manole, A. Ramdas       arxiv   video   (Student Research Award, Statistical Society of Canada)

• Estimating means of bounded random variables by betting
  I. Waudby-Smith, A. Ramdas       JRSSB, 2023   arxiv   (Discussion paper)

• Admissible anytime-valid sequential inference must rely on nonnegative martingales
  A. Ramdas, J. Ruf, M. Larsson, W. Koolen       arxiv

• Time-uniform central limit theory, asymptotic confidence sequences and anytime-valid causal inference
  I. Waudby-Smith, D. Arbour, R. Sinha, E. Kennedy, A. Ramdas       arxiv   package  

• Testing exchangeability: fork-convexity, supermartingales, and e-processes
  A. Ramdas, J. Ruf, M. Larsson, W. Koolen       Intl J of Approximate Reasoning, 2022   arxiv   proc

• Tracking the risk of a deployed model and detecting harmful distribution shifts
  A. Podkopaev, A. Ramdas       ICLR, 2022   arxiv   proc

• Uncertainty quantification using martingales for misspecified Gaussian processes
  W. Neiswanger, A. Ramdas       Algorithmic Learning Theory (ALT), 2021   arxiv   code   talk   proc

• RiLACS: Risk-limiting audits via confidence sequences
  I. Waudby-Smith, P. Stark, A. Ramdas       EVoteID, 2021   arxiv   (Best Paper award)

• Nonparametric iterated-logarithm extensions of the sequential generalized likelihood ratio test
  J. Shin, A. Ramdas, A. Rinaldo       IEEE J. on Selected Areas in Info. Theory, 2021   arxiv   proc

• Confidence sequences for sampling without replacement
  I. Waudby-Smith, A. Ramdas       NeurIPS, 2020   arxiv   app-continuous   app-discrete   proc

• Universal inference
  L. Wasserman, A. Ramdas, S. Balakrishnan       PNAS, 2020   arxiv   proc   talk

• Sequential estimation of quantiles with applications to A/B-testing and best-arm identification
  S. Howard, A. Ramdas       Bernoulli, 2022   arxiv   code   proc

• Time-uniform, nonparametric, nonasymptotic confidence sequences
  S. Howard, A. Ramdas, J. Sekhon, J. McAuliffe       The Annals of Stat., 2021   arxiv   proc   code   tutorial

• Time-uniform Chernoff bounds via nonnegative supermartingales
  S. Howard, A. Ramdas, J. Sekhon, J. McAuliffe       Prob. Surveys, 2020   arxiv   proc   talk

• Sequential nonparametric testing with the law of the iterated logarithm
  A. Balsubramani*, A. Ramdas*       Uncertainty in AI, 2016   arxiv   proc   errata

Privacy

• Fully adaptive composition in differential privacy
  J. Whitehouse, A. Ramdas, R. Rogers, Z.S. Wu       arxiv  

• Brownian noise reduction: maximizing privacy subject to accuracy constraints
  J. Whitehouse, Z.S. Wu, A. Ramdas, R. Rogers       NeurIPS, 2022   arxiv  

• Locally private nonparametric confidence intervals and sequences
  I. Waudby-Smith, S. Wu, A. Ramdas       arxiv  

• Brainprints: identifying individuals from magnetoencephalograms
  S. Wu, A. Ramdas, L. Wehbe       Nature Communications Biology, 2022   bioRxiv   proc

Multi-armed bandits

• Off-policy confidence sequences
  N. Karampatziakis, P. Mineiro, A. Ramdas       ICML, 2021   arxiv  

• A unified framework for bandit multiple testing
  Z. Xu, R. Wang, A. Ramdas       NeurIPS, 2021   arxiv   proc

• Post-selection inference for e-value based confidence intervals
  Z. Xu, R. Wang, A. Ramdas       arxiv  

• Best Arm Identification under Additive Transfer Bandits
  O. Neopane, A. Singh, A. Ramdas       Asilomar, 2021   (Best Student Paper award) arxiv   proc

• On conditional versus marginal bias in multi-armed bandits
  J. Shin, A. Ramdas, A. Rinaldo       ICML, 2020   arxiv   proc

• Are sample means in multi-armed bandits positively or negatively biased?
  J. Shin, A. Ramdas, A. Rinaldo       NeurIPS, 2019   arxiv   poster   proc

• On the bias, risk and consistency of sample means in multi-armed bandits
  J. Shin, A. Ramdas, A. Rinaldo       SIAM J Math of Data Science (SIMODS), 2021   arxiv   talk   proc

• MAB-FDR: Multi (A)rmed/(B)andit testing with online FDR control
  F. Yang, A. Ramdas, K. Jamieson, M. Wainwright       NeurIPS, 2017   arxiv   code   30-min talk   proc   (spotlight talk)

Online multiple testing (package) (vignette) (shiny app, FDR) (shiny app, FWER)

• Online multiple hypothesis testing for reproducible research
  D. Robertson, J. Wason, A. Ramdas       arxiv  

• Dynamic algorithms for online multiple testing
  Z. Xu, A. Ramdas       Mathematical and Scientific ML, 2021   arxiv   proc

• ADDIS: an adaptive discarding algorithm for online FDR control with conservative nulls
  J. Tian, A. Ramdas       NeurIPS, 2019   arxiv   code   proc

• Online control of the false coverage rate and false sign rate
  A. Weinstein*, A. Ramdas*       ICML, 2020   arxiv   proc

• Online control of the familywise error rate
  J. Tian*, A. Ramdas*       Statistical Methods in Medical Research, 2021   arxiv   proc

• Asynchronous online testing of multiple hypotheses
  T. Zrnic, A. Ramdas, M. Jordan       JMLR, 2021   arxiv   code   blog   proc

• The power of batching in multiple hypothesis testing
  T. Zrnic, D. Jiang, A. Ramdas, M. Jordan       AISTATS, 2020   arxiv   talk   proc

• SAFFRON: an adaptive algorithm for online FDR control
  A. Ramdas, T. Zrnic, M. Wainwright, M. Jordan       ICML, 2018   arxiv   proc   github   (full oral talk)

• Online control of the false discovery rate with decaying memory
  A. Ramdas, F. Yang, M. Wainwright, M. Jordan       NeurIPS, 2017   arxiv   summary   poster   proc   15-min from 44:00   (full oral talk)

Interactive/dynamic multiple testing

• Data fission: splitting a single data point
  J. Leiner, B. Duan, L. Wasserman, A. Ramdas       arxiv

• Interactive identification of individuals with positive treatment effect while controlling false discoveries
  B. Duan, L. Wasserman, A. Ramdas       arxiv  

• STAR: A general interactive framework for FDR control under structural constraints
  L. Lei, A. Ramdas, W. Fithian       Biometrika, 2020   arxiv   proc   poster   code

• Familywise error rate control by interactive unmasking
  B. Duan, A. Ramdas, L. Wasserman       ICML, 2020   arxiv   code

• Interactive martingale tests for the global null
  B. Duan, A. Ramdas, S. Balakrishnan, L. Wasserman       Electronic J. of Stat., 2020   arxiv   code   proc

• Interactive rank testing by betting
  B. Duan, L. Wasserman, A. Ramdas       Causal Learning and Reasoning (CLEAR), 2022   arxiv   proc

• Simultaneous high-probability bounds on the FDP in structured, regression and online settings
  E. Katsevich, A. Ramdas       Annals of Stat., 2020   arxiv   code   proc

• Large-scale simultaneous inference under dependence
  J. Tian, X. Chen, E. Katsevich, J. Goeman, A. Ramdas       Scandanavian J of Stat., 2022   arxiv   proc

• QuTE: decentralized FDR control on sensor networks
  A. Ramdas, J. Chen, M. Wainwright, M. Jordan       IEEE CDC, 2017   arXiv code   proc   poster

Offline multiple testing

• E-values as unnormalized weights in multiple testing
  N. Ignatiadis, R. Wang, A. Ramdas       arxiv  

• False discovery rate control with e-values
  R. Wang, A. Ramdas       J of Royal Stat. Soc., Series B, 2022   arxiv   proc

• Fast and powerful conditional randomization testing via distillation
  M. Liu, E. Katsevich, L. Janson, A. Ramdas       Biometrika, 2021   arxiv   code   proc

• A unified treatment of multiple testing with prior knowledge using the p-filter
  A. Ramdas, R. F. Barber, M. Wainwright, M. Jordan       Annals of Stat., 2019   arxiv   code   proc

• DAGGER: A sequential algorithm for FDR control on DAGs
  A. Ramdas, J. Chen, M. Wainwright, M. Jordan       Biometrika, 2019   arxiv   code   proc

• Optimal rates and tradeoffs in multiple testing
  M. Rabinovich, A. Ramdas, M. Wainwright, M. Jordan       Stat. Sinica, 2019   arxiv   poster   proc

• p-filter: multi-layer FDR control for grouped hypotheses
  R. F. Barber*, A. Ramdas*       J of Royal Stat. Soc., Series B, 2016   arxiv   code   proc   poster

High-dimensional/nonparametric testing

• Dimension-agnostic inference using cross U-statistics
  I. Kim, A. Ramdas       arxiv

• A permutation-free kernel two sample test
  S. Shekhar, I. Kim, A. Ramdas       Neurips, 2022  

• Gaussian universal likelihood ratio testing
  R. Dunn, A. Ramdas, S. Balakrishnan, L. Wasserman       Biometrika, 2022   arxiv  

• Universal inference meets random projections: a scalable test for log-concavity
  R. Dunn, A. Gangrade, L. Wasserman, A. Ramdas       arxiv

• On the power of conditional independence testing under model-X
  E. Katsevich, A. Ramdas       Elec J Stat, 2023   arxiv

• Adaptivity & computation-statistics tradeoffs for kernel & distance based high-dimensional two sample testing
  A. Ramdas, S. Reddi, B. Poczos, A. Singh, L. Wasserman       arxiv   poster  

• Classification accuracy as a proxy for two sample testing
  I. Kim*, A. Ramdas*, A. Singh, L. Wasserman       Annals of Stat., 2021   arxiv   proc   (JSM Stat Learning Student Paper Award)

• Minimax lower bounds for linear independence testing
  D. Isenberg*, A. Ramdas*, A. Singh, L. Wasserman       IEEE ISIT, 2016   arxiv   proc

• On the high-dimensional power of a linear-time two sample test under mean-shift alternatives
  S. Reddi*, A. Ramdas*, A. Singh, B. Poczos, L. Wasserman       AISTATS, 2015   proc   arxiv   errata

• On the decreasing power of kernel and distance based nonparametric hypothesis tests in high dimensions
  A. Ramdas*, S. Reddi*, B. Poczos, A. Singh, L. Wasserman       AAAI, 2015   proc   arxiv   supp

• A higher order Kolmogorov Smirnov test
  V. Sadhanala, Y. Wang, A. Ramdas, R. Tibshirani       AISTATS, 2019   arxiv   proc

• On Wasserstein two sample testing and related families of nonparametric tests
  A. Ramdas*, N. Garcia*, M. Cuturi       Entropy, 2017 (Special Issue)   arxiv   proc   SI

• Generative models and model criticism via optimized Maximum Mean Discrepancy
  D. Sutherland, H. Tung, H. Strathmann, S. De, A. Ramdas, A. Smola, A. Gretton       ICLR, 2017   arxiv   proc   poster   code

• Fast two-sample testing with analytic representations of probability measures
  K. Chwialkowski, A. Ramdas, D. Sejdinovic, A. Gretton       NeurIPS, 2015   arxiv   github   proc

• Nonparametric independence testing for small sample sizes
  A. Ramdas*, L. Wehbe*       IJCAI, 2015   arxiv   proc   (oral talk)

Distribution-free uncertainty quantification (conformal, calibration) (package) (package 2) (tutorial)

• Permutation tests using arbitrary permutation distributions
  A. Ramdas, R. Barber, E. Candes, R. Tibshirani       arxiv  

• Faster online calibration without randomization: interval forecasts and the power of two choices
  C. Gupta, A. Ramdas       COLT, 2022   arxiv  

• Conformal prediction beyond exchangeability
  R. Barber, E. Candes, A. Ramdas, R. Tibshirani       arxiv  

• Top-label calibration and multiclass-to-binary reductions
  C. Gupta, A. Ramdas       ICLR, 2022   arxiv  

• Distribution-free calibration guarantees for histogram binning without sample splitting
  C. Gupta, A. Ramdas       ICML, 2021   arxiv   proc

• Distribution-free uncertainty quantification for classification under label shift
  A. Podkopaev, A. Ramdas       UAI, 2021   arxiv   proc

• Distribution-free binary classification: prediction sets, confidence intervals and calibration
  C. Gupta, A. Podkopaev, A. Ramdas       NeurIPS, 2020   arxiv   proc  

• Nested conformal prediction and quantile out-of-bag ensemble methods
  C. Gupta, A. Kuchibhotla, A. Ramdas       Pattern Recognition, 2022   arxiv   code   proc

• The limits of distribution-free conditional predictive inference
  R. Barber, E. Candes, A. Ramdas, R. Tibshirani       Information and Inference, 2020   arxiv   proc

• Conformal prediction under covariate shift
  R. Tibshirani, R. Barber, E. Candes, A. Ramdas       NeurIPS, 2019   arxiv   proc   poster  

• Predictive inference with the jackknife+
  R. Barber, E. Candes, A. Ramdas, R. Tibshirani       Annals of Stat., 2021   arxiv   code   proc

• Distribution-free prediction sets for two-layer hierarchical models
  R. Dunn, L. Wasserman, A. Ramdas       J of American Stat. Assoc., 2022   arxiv   proc

Convex optimization

• Path length bounds for gradient descent and flow
  C. Gupta, S. Balakrishnan, A. Ramdas       JMLR, 2021   arxiv   proc   blog

• Iterative methods for solving factorized linear systems
  A. Ma, D. Needell, A. Ramdas       SIAM J on Matrix Anal. and App., 2017   arxiv   proc

• Rows vs columns : randomized Kaczmarz or Gauss-Seidel for ridge regression
  A. Hefny*, D. Needell*, A. Ramdas*       SIAM J on Sci. Comp., 2017   arxiv   proc

• Convergence properties of the randomized extended Gauss-Seidel and Kaczmarz methods
  A. Ma*, D. Needell*, A. Ramdas*       SIAM J on Matrix Anal. and App., 2015   arxiv   proc   code

• Fast & flexible ADMM algorithms for trend filtering
  A. Ramdas*, R. Tibshirani*       J of Comp. and Graph. Stat., 2015   arxiv   proc   github ‘glmgen’   50 min. talk

• Towards a deeper geometric, analytic and algorithmic understanding of margins
  A. Ramdas, J. Pena       Opt. Methods and Software, 2015   arxiv   proc

• Margins, kernels and non-linear smoothed perceptrons
  A. Ramdas, J. Pena       ICML, 2014   arxiv   proc   poster   (oral talk)

• Algorithmic connections between active learning and stochastic convex optimization
  A. Ramdas, A. Singh       Alg. Learning Theory, 2013   arxiv   proc   poster  

• Optimal rates for stochastic convex optimization under Tsybakov's noise condition
  A. Ramdas, A. Singh       ICML, 2013   proc   arxiv   poster   (oral talk)

One-off projects

• Analyzing student strategies in blended courses using clickstream data
  N. Akpinar, A. Ramdas, U. Acar       Educational Data Mining, 2020   arxiv   talk  

• Function-specific mixing times and concentration away from equilibrium
  M. Rabinovich, A. Ramdas, M. Wainwright, M. Jordan       Bayesian Analysis, 2019   arxiv   proc   poster  

• Decoding from pooled data (II): sharp information-theoretic bounds
  A. El-Alaoui, A. Ramdas, F. Krzakala, L. Zdeborova, M. Jordan       SIAM J on Math. of Data Science, 2019   arxiv   proc

• Decoding from pooled data (I): phase transitions of message passing
  A. El-Alaoui, A. Ramdas, F. Krzakala, L. Zdeborova, M. Jordan       IEEE Trans. on Info. Theory, 2018   arxiv   proc

• On the power of online thinning in reducing discrepancy
  R. Dwivedi, O. N. Feldheim, Ori Gurel-Gurevich, A. Ramdas       Prob. Theory and Related Fields, 2018   arxiv   poster   proc

• On kernel methods for covariates that are rankings
  H. Mania, A. Ramdas, M. Wainwright, M. Jordan, B. Recht       Electronic J of Stat., 2018   arxiv   proc

• Asymptotic behavior of Lq-based Laplacian regularization in semi-supervised learning
  A. El-Alaoui, X. Cheng, A. Ramdas, M. Wainwright, M. Jordan       COLT, 2016   arxiv   proc

• Regularized brain reading with shrinkage and smoothing
  L. Wehbe, A. Ramdas, R. Steorts, C. Shalizi       Annals of App. Stat., 2015   arxiv   proc

• Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses
  L. Wehbe, B. Murphy, P. Talukdar, A. Fyshe, A. Ramdas, T. Mitchell       PLoS ONE, 2014   website   proc  

• An analysis of active learning with uniform feature noise
  A. Ramdas, A. Singh, L. Wasserman, B. Poczos       AISTATS, 2014   arxiv   proc   poster   (oral talk)  

Miscellaneous

• Discussion: Testing by betting
  A. Ramdas       JRSSB, 2020   proc

• Discussion: Covariate-assisted ranking and screening for large-scale two-sample inference
  A. Ramdas       JRSSB, 2019   proc

• Algorithms for graph similarity and subgraph matching
  D. Koutra, A. Parikh, A. Ramdas, J. Xiang       Tech Report   pdf