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DTSTART:20210328T030000
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DTSTAMP:20260404T203413Z
UID:1623852000@ist.ac.at
DTSTART:20210616T160000
DTEND:20210616T170000
DESCRIPTION:Speaker: Dan Alistarh\nhosted by Chris Wojtan\nAbstract: Distri
 bution has been a major trend in computing over the last two decades\, and
  has enabled a wide range of applications\, from the fast training of larg
 e-scale machine learning models\, to cloud services which can process our 
 requests within milliseconds. In this talk\, I will describe some of the b
 asic ideas underpinning these applications\, in the context of the work do
 ne by our lab. Specifically\, I will first describe the role of efficient 
 distributed algorithms in machine learning\, as well as the intriguing tra
 de-offs between their synchronization costs and their convergence properti
 es. Second\, I will discuss our work on scalable variants of classic data 
 structures such as priority queues and search trees\, as well as on popula
 tion protocols\, roughly defined as distributed algorithms which can be im
 plemented at molecular scale.
LOCATION:Online\, ISTA
ORGANIZER:arinya.eller@ist.ac.at
SUMMARY:Dan Alistarh: Scalable distributed algorithms and systems
URL:https://talks-calendar.ista.ac.at/events/3197
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