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SUMMARY:Perception-Driven Optimization: A New Frontier for Scaling Interne
 t Applications - Junchen Jiang\, University of Chicago
DTSTART:20220210T150000Z
DTEND:20220210T160000Z
UID:TALK163285@talks.cam.ac.uk
CONTACT:Srinivasan Keshav
DESCRIPTION:A computational approach to human perception has sparked break
 throughs in AI\, human-computer interaction\, and social cognition. In thi
 s talk\, I will introduce attention-driven resource allocation\, a transfo
 rmative paradigm that improve perceived quality for human users (e.g.\, vi
 deo streaming) as well as emerging AI applications (e.g.\, real-time video
  analytics). In contrast to today's network systems that optimize handcraf
 ted performance metrics\, we advocate that network systems should align re
 source allocation with user attention. The insight is that video viewers o
 r web users rarely perceive application quality by consciously measuring m
 etrics such as video rebuffering time or web page load time\; instead\, th
 ey react the visual process of video rendering or page loading. Similarly\
 , computer vision applications\, though highly data-/compute-intensive\, d
 o not require high quality data everywhere or all the time. This talk will
  use a few case studies from our recent work to present early attempts and
  promises of attention-driven systems.\n\nBio:\nJunchen Jiang is an Assist
 ant Professor of Computer Science at the University of Chicago. He receive
 d his PhD degree from Carnegie Mellon University in 2017 and his bachelor'
 s degree from Tsinghua Univ in 2011. His research interests are networked 
 systems and their intersections with machine learning. He is a recipient o
 f Google Faculty Research Award in 2019\, best Paper Award at the Symposiu
 m of Edge Computing in 2020\, and CMU Computer Science Doctoral Dissertati
 on Award in 2017.
LOCATION:FW11 and https://cl-cam-ac-uk.zoom.us/j/97216272378?pwd=M2diTFhMT
 nppckJtNWhFVTBKK0REZz09
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