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DTSTAMP:20240209T174021Z
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DESCRIPTION:The primary objective of data processing applications is to der
 ive statistical inferences from data and subsequently perform statistical 
 tasks\, addressing communication and computation constraints\, as well as 
 privacy and security concerns. In this presentation\, I will begin by disc
 ussing statistical approaches applied to the perceptual quality of images 
 and videos in the context of compression tasks. This is particularly relev
 ant in applications such as online video streaming\, where statistical too
 ls play a crucial role in extracting information from newly available fram
 es in a casual manner and propagating it for future reconstructions. I wil
 l explore two perception loss functions\, highlighting their differences b
 ased on the reconstructions of consecutive frames. Next\, I will delve int
 o statistical inference within large networks of agents\, emphasizing the 
 necessity for adaptive decision-making to handle data under communication 
 constraints. Additionally\, I will briefly touch upon privacy and security
  challenges inherent in these two networks. To conclude\, I will summarize
  the presentation and propose research directions aimed at addressing both
  statistical and privacy/security challenges.\n\nSpeaker(s): Sadaf Salehka
 laibar\, \n\nAgenda: \n11:00 AM Start of talk\n12:00 PM Conclusion\n\nVirt
 ual: https://events.vtools.ieee.org/m/405728
LOCATION:Virtual: https://events.vtools.ieee.org/m/405728
ORGANIZER:sharan.kalwani@ieee.org
SEQUENCE:13
SUMMARY:Statistical Machine Learning in Data Processing: Challenges and Opp
 ortunities
URL;VALUE=URI:https://events.vtools.ieee.org/m/405728
X-ALT-DESC:Description: <br /><p>The primary objective of data processing a
 pplications is to derive statistical inferences from data and subsequently
  perform statistical tasks\, addressing communication and computation cons
 traints\, as well as privacy and security concerns. In this presentation\,
  I will begin by discussing statistical approaches applied to the perceptu
 al quality of images and videos in the context of compression tasks. This 
 is particularly relevant in applications such as online video streaming\, 
 where statistical tools play a crucial role in extracting information from
  newly available frames in a casual manner and propagating it for future r
 econstructions. I will explore two perception loss functions\, highlightin
 g their differences based on the reconstructions of consecutive frames. Ne
 xt\, I will delve into statistical inference within large networks of agen
 ts\, emphasizing the necessity for adaptive decision-making to handle data
  under communication constraints. Additionally\, I will briefly touch upon
  privacy and security challenges inherent in these two networks. To conclu
 de\, I will summarize the presentation and propose research directions aim
 ed at addressing both statistical and privacy/security challenges.</p><br 
 /><br />Agenda: <br /><p>11:00 AM Start of talk<br />12:00 PM Conclusion</
 p>
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