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UID:www.tcs.tifr.res.in/event/1123
DTSTAMP:20230914T125951Z
SUMMARY:Generalization and Guessing
DESCRIPTION:Speaker: Eeshan Modak\n\nAbstract: \nAbstract: Generalization e
 rror is the gap between an algorithm's performance on the true data distri
 bution (unknown to us) and its performance on the given dataset (known to 
 us). Thus\, establishing upper bounds on generalization error is naturally
  of interest. In 2020\, Steinke and Zakynthinou derived their bound in ter
 ms of the ability to guess an algorithm's input by observing its output. I
 n this talk\, we will try to go over the proof of this result.\nLink to th
 e paper: https://arxiv.org/abs/2001.09122\n\nZoom link:\nhttps://zoom.us/j
 /98132227553?pwd=K2cyQllKVjExdUhlRm0vc0ZHcEt0Zz09\n
URL:https://www.tcs.tifr.res.in/web/events/1123
DTSTART;TZID=Asia/Kolkata:20210326T171500
DTEND;TZID=Asia/Kolkata:20210326T181500
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