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X-WR-RELCALID:efc09d74-9c93-479e-a94f-485231ddccde
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X-WR-CALNAME:Stochastic Approximation Algorithms with Decision-Dependent Da
 ta: The Case of Performative Prediction - Hoi-To Wai\, Assistant Professor
 \, CUHK
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TZID:America/Vancouver
TZUNTIL:20261101T090000Z
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DTSTART:20241103T020000
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DTSTAMP:20260122T165427Z
CLASS:PUBLIC
CREATED:20241206T222743Z
DESCRIPTION:Abstract: Stochastic approximation (SA) forms the foundation of
  numerous online decision-making algorithms under uncertainty. In recent y
 ears\, it has garnered renewed interest in the dynamic environment setting
  where streaming data is not independent and identically distributed (i.i.
 d.)\, but rather correlated and/or decision-dependent. This resurgence of 
 interest stems from its widespread application in contemporary domains\, s
 uch as reinforcement learning\, performative prediction\, and fine-tuning 
 of large language models (LLMs). This presentation focuses on SA algorithm
 s applied to stochastic…
DTSTART;TZID=America/Vancouver:20241213T100000
DTEND;TZID=America/Vancouver:20241213T110000
LAST-MODIFIED:20241206T225452Z
LOCATION:UBC Vancouver Campus\, ICCS 288
SUMMARY:Stochastic Approximation Algorithms with Decision-Dependent Data: T
 he Case of Performative Prediction - Hoi-To Wai\, Assistant Professor\, CU
 HK
TRANSP:OPAQUE
URL:https://caida.ubc.ca/event/stochastic-approximation-algorithms-decision
 -dependent-data-case-performative-prediction-hoi
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