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Summary

DescriptionRelativeRankLearning2.pdf
English: Learning in the partial-information sequential search paradigm. The numbers display the expected values of applicants based on their relative rank (out of m total applicants seen so far) at various points in the search. Expectations are calculated based on the case when their values are uniformly distributed between 0 and 1. Relative rank information allows the interviewer to more finely evaluate applicants as they accumulate more data points to compare them to.
Date
Source Own work
Author Wholewheat7

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Expected values of applicants based on their relative rank (out of m total applicants seen so far) at various points in the search, for the case when their values are uniformly distributed between 0 and 1.

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Date/TimeThumbnailDimensionsUserComment
current19:28, 18 March 2021 Thumbnail for version as of 19:28, 18 March 2021 1,650 ×ばつ 1,275 (263 KB)Wholewheat7 rotated to correct
19:22, 18 March 2021 No thumbnail0 ×ばつ 0 (262 KB)Wholewheat7 Uploaded own work with UploadWizard

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Short titleRelativeRankLearning
Software usedPreview
Conversion programmacOS Version 11.2.1 (Build 20D74) Quartz PDFContext, AppendMode 1.1
Encryptedno
Page size612 x 792 pts (letter)
Version of PDF format1.3

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