Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Aaditya Ramdas"'
Publikováno v:
Communications Biology, Vol 5, Iss 1, Pp 1-12 (2022)
Analysis of spatial, temporal, and frequency features through different datasets show that magnetoencephalogram data can be used to uniquely identify an individual among a group.
Externí odkaz:
https://doaj.org/article/3ef5dbdda17140d1983b3865b16f0c22
Publikováno v:
Entropy, Vol 19, Iss 2, p 47 (2017)
Nonparametric two-sample or homogeneity testing is a decision theoretic problem that involves identifying differences between two random variables without making parametric assumptions about their underlying distributions. The literature is old and r
Externí odkaz:
https://doaj.org/article/089cd3d1923c432d83dc31b67447fe11
Publikováno v:
PLoS ONE, Vol 9, Iss 11, p e112575 (2014)
Story understanding involves many perceptual and cognitive subprocesses, from perceiving individual words, to parsing sentences, to understanding the relationships among the story characters. We present an integrated computational model of reading th
Externí odkaz:
https://doaj.org/article/1766b32541f34ebc9dcbf3f3a9dd3f6b
Publikováno v:
Biometrika. 110:319-337
The classical likelihood ratio test (LRT) based on the asymptotic chi-squared distribution of the log likelihood is one of the fundamental tools of statistical inference. A recent universal LRT approach based on sample splitting provides valid hypoth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::889b39afd5572e1a7bffeee71003ba61
https://doi.org/10.1093/biomet/asac064
https://doi.org/10.1093/biomet/asac064
Publikováno v:
Stat. 12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ac2adb7f1d91a93b26380d2b4730fa3
https://doi.org/10.1002/sta4.573
https://doi.org/10.1002/sta4.573
Publikováno v:
International Journal of Approximate Reasoning, 141, 83-109
Suppose we observe an infinite series of coin flips $X_1,X_2,\ldots$, and wish to sequentially test the null that these binary random variables are exchangeable. Nonnegative supermartingales (NSMs) are a workhorse of sequential inference, but we prov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14db015f8a7ccd465bbd7acc6a6f0375
https://ir.cwi.nl/pub/33117
https://ir.cwi.nl/pub/33117
Autor:
Akash Maharaj, Ritwik Sinha, David Arbour, Ian Waudby-Smith, Simon Z. Liu, Moumita Sinha, Raghavendra Addanki, Aaditya Ramdas, Manas Garg, Viswanathan Swaminathan
A/B tests are the gold standard for evaluating digital experiences on the web. However, traditional "fixed-horizon" statistical methods are often incompatible with the needs of modern industry practitioners as they do not permit continuous monitoring
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14e11b455a6dfa17d4b1240212604418
Publikováno v:
Communications Biology. 5
Magnetoencephalography (MEG) is used to study a wide variety of cognitive processes. Increasingly, researchers are adopting principles of open science and releasing their MEG data. While essential for reproducibility, sharing MEG data has unforeseen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7ce34801053eb0912f1e7d05413c14d
https://doi.org/10.1038/s42003-022-03727-9
https://doi.org/10.1038/s42003-022-03727-9
Publikováno v:
Biometrika. 108:253-267
Summary We propose a general framework based on selectively traversed accumulation rules for interactive multiple testing with generic structural constraints on the rejection set. It combines accumulation tests from ordered multiple testing with data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f521a23dfdb1bcec58e33c8d42e86d5
https://doi.org/10.1093/biomet/asaa064
https://doi.org/10.1093/biomet/asaa064
Autor:
Tudor Manole, Aaditya Ramdas
Publikováno v:
IEEE Transactions on Information Theory. :1-1
We present a unified technique for sequential estimation of convex divergences between distributions, including integral probability metrics like the kernel maximum mean discrepancy, $\varphi$-divergences like the Kullback-Leibler divergence, and opt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c82b46788ffed3733690d777968ad150
https://doi.org/10.1109/tit.2023.3250099
https://doi.org/10.1109/tit.2023.3250099