Aaditya Ramdas – Publications


Anytime-valid, safe confidence intervals and p-values (package)

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

  • Uniform, nonparametric, nonasymptotic confidence sequences
    S. Howard, A. Ramdas, J. Sekhon, J. McAuliffe   arxiv   talk

  • Exponential line-crossing inequalities
    S. Howard, A. Ramdas, J. Sekhon, J. McAuliffe   arxiv

  • Sequential nonparametric testing with the law of the iterated logarithm
    A. Balsubramani*, A. Ramdas*
    (UAI) Uncertainty in Artificial Intelligence, 2016   arxiv   UAI   errata


Multi-armed bandits

  • Are sample means in multi-armed bandits positively or negatively biased?
    J. Shin, A. Ramdas, A. Rinaldo  
    (NeurIPS) Neural Information Processing Systems, 2019   arxiv

  • On the bias, risk and consistency of sample means in multi-armed bandits
    J. Shin, A. Ramdas, A. Rinaldo   arxiv   talk

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


Online multiple hypothesis testing (package)

  • ADDIS: an adaptive discarding algorithm for online FDR control with conservative nulls
    J. Tian, A. Ramdas  
    (NeurIPS) Neural Information Processing Systems, 2019   arxiv   code

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

  • Online control of the familywise error rate
    J. Tian*, A. Ramdas*   arxiv

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

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

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

  • Online control of the false discovery rate with decaying memory
    A. Ramdas, F. Yang, M. Wainwright, M. Jordan
    (NeurIPS) Neural Information Processing Systems, 2017   arxiv   3-min summary   NeurIPS   15-min talk from 44:00   (full oral talk)


Interactive/dynamic multiple testing

  • Interactive martingale tests for the global null
    B. Duan, A. Ramdas, S. Balakrishnan, L. Wasserman   arxiv

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

  • STAR: A general interactive framework for FDR control under structural constraints
    L. Lei, A. Ramdas, W. Fithian   arxiv   movies

  • QuTE: decentralized FDR control on sensor networks
    A. Ramdas, J. Chen, M. Wainwright, M. Jordan
    (CDC) IEEE Conference on Decision and Control, 2017   code   CDC


Offline multiple testing

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

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

  • Optimal rates and tradeoffs for multiple testing
    M. Rabinovich, A. Ramdas, M. Wainwright, M. Jordan
    (SS) Statistica Sinica, 2019   arxiv

  • p-filter: multi-layer FDR control for grouped hypotheses
    R. F. Barber*, A. Ramdas*
    (JRSSB) Journal of the Royal Statistical Society, Series B (Methodology), 2016   arxiv   code   JRSSB


High-dimensional hypothesis testing

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

  • Classification accuracy as a proxy for two sample testing
    I. Kim*, A. Ramdas*, A. Singh, L. Wasserman   arxiv

  • Minimax lower bounds for linear independence testing
    D. Isenberg*, A. Ramdas*, A. Singh, L. Wasserman
    (ISIT) IEEE International Symposium on Information Theory, 2016   arxiv   ISIT

  • 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) International Conference on Artificial Intelligence and Statistics, 2015   AISTATS   arxiv   pdf   supp   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) AAAI Conference on Artifical Intelligence, 2015   AAAI   arxiv   pdf   supp


Nonparametric hypothesis testing

  • A higher order Kolmogorov Smirnov test
    V. Sadhanala, Y. Wang, A. Ramdas, R. Tibshirani
    (AISTATS) 22nd International Conference on Artificial Intelligence and Statistics, 2019   arxiv   PMLR

  • On Wasserstein two sample testing and related families of nonparametric tests
    A. Ramdas*, N. Garcia*, M. Cuturi
    (Ent) Entropy, Special Issue on Statistical Significance and the Logic of Hypothesis Testing, 2017   arxiv   Entropy

  • 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) International Conference on Learning Representations, 2017   arxiv   ICLR   poster   code

  • Fast two-sample testing with analytic representations of probability measures
    K. Chwialkowski, A. Ramdas, D. Sejdinovic, A. Gretton
    (NeurIPS) Neural Information Processing Systems, 2015   arxiv   github   NeurIPS

  • Nonparametric independence testing for small sample sizes
    A. Ramdas*, L. Wehbe*
    (IJCAI) International Joint Conference on Artificial Intelligence, 2015   arxiv   IJCAI   (oral talk)


Conformal prediction and exchangeability (package)

  • Nested conformal prediction and the generalized jackknife+
    A. Kuchibhotla, A. Ramdas   arxiv

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

  • Conformal prediction under covariate shift
    R. Tibshirani, R. Barber, E. Candes, A. Ramdas  
    (NeurIPS) Neural Information Processing Systems, 2019   arxiv

  • Predictive inference with the jackknife+
    R. Barber, E. Candes, A. Ramdas, R. Tibshirani   arxiv   code


Solving large linear systems

  • Iterative methods for solving factorized linear systems
    A. Ma, D. Needell, A. Ramdas
    (SIMAX) SIAM Journal on Matrix Analysis and Applications, 2017   arxiv   SIMAX

  • Rows vs columns : randomized Kaczmarz or Gauss-Seidel for ridge regression
    A. Hefny*, D. Needell*, A. Ramdas*
    (SISC) SIAM Journal on Scientific Computing, 2017   arxiv   SISC

  • Convergence properties of the randomized extended Gauss-Seidel and Kaczmarz methods
    A. Ma*, D. Needell*, A. Ramdas*
    (SIMAX) SIAM Journal on Matrix Analysis and Applications, 2015   arxiv   SIMAX   code


Convex optimization

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

  • Towards a deeper geometric, analytic and algorithmic understanding of margins
    A. Ramdas, J. Pena
    (OMS) Optimization Methods and Software, 2015   arxiv   OMS

  • Margins, kernels and non-linear smoothed perceptrons
    A. Ramdas, J. Pena
    (ICML) International Conference on Machine Learning, 2014   arxiv   ICML   pdf   supp   (oral talk)

  • Algorithmic connections between active learning and stochastic convex optimization
    A. Ramdas, A. Singh
    (ALT) International Conference on Algorithmic Learning Theory, 2013   arxiv   ALT  

  • Optimal rates for stochastic convex optimization under Tsybakov's noise condition
    A. Ramdas, A. Singh
    (ICML) International Conference on Machine Learning, 2013   ICML   arxiv   pdf   supp   (oral talk)


Scientific collaborations

  • Regularized brain reading with shrinkage and smoothing
    L. Wehbe, A. Ramdas, R. Steorts, C. Shalizi
    (AoAS) Annals of Applied Statistics, 2015   arxiv   AoAS

  • 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) Public Library of Science ONE, 2014   website   PLOS  


One-off projects

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

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

  • Decoding from pooled data (I): phase transitions of message passing
    A. El-Alaoui, A. Ramdas, F. Krzakala, L. Zdeborova, M. Jordan
    (ITIT) IEEE Transactions on Information Theory, 2018 (shorter version, ISIT 2017)   arxiv   IEEE

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

  • On kernel methods for covariates that are rankings
    H. Mania, A. Ramdas, M. Wainwright, M. Jordan, B. Recht
    (EJS) Electronic Journal of Statistics, 2018   arxiv   EJS

  • Asymptotic behavior of Lq-based Laplacian regularization in semi-supervised learning
    A. El-Alaoui, X. Cheng, A. Ramdas, M. Wainwright, M. Jordan
    (COLT) International Conference on Learning Theory, 2016   arxiv   COLT

  • An analysis of active learning with uniform feature noise
    A. Ramdas, A. Singh, L. Wasserman, B. Poczos
    (AISTATS) International Conference on Artificial Intelligence and Statistics, 2014   arxiv   AISTATS   pdf   supp   (oral talk)


Miscellaneous

  • Discussion: Covariate-assisted ranking and screening for large-scale two-sample inference
    A. Ramdas
    (JRSSB) Journal of the Royal Statistical Society, Series B, 2019  

  • Computational and Statistical Advances in Testing and Learning
    A. Ramdas
    (PhD thesis)   pdf   (Umesh K. Gavaskar Memorial Thesis Award)

  • Analysis of burglaries in Pittsburgh
    A. Ramdas
    (Project)   pdf

  • Algorithms for graph similarity and subgraph matching
    D. Koutra, A. Parikh, A. Ramdas, J. Xiang
    (Project)   pdf

  • Termination of single-loop linear programs
    A. Ramdas
    (UG thesis)   pdf