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X-WR-TIMEZONE:America/Vancouver
X-WR-CALNAME:Predicting human decisions with behavioral theories and machin
 e learning - Ori Plonsky\, Assistant Professor\, Technion-Israel Institute
  of Technology
BEGIN:VTIMEZONE
TZID:America/Vancouver
TZUNTIL:20261101T090000Z
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DTSTART:20241103T020000
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TZOFFSETTO:-0800
RDATE:20251102T020000
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RDATE:20260308T020000
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DTSTAMP:20260227T084948Z
CLASS:PUBLIC
CREATED:20241211T000244Z
DESCRIPTION:Abstract: Predicting human decision-making under risk and uncer
 tainty remains a core challenge in economics\, psychology\, and related fi
 elds. Despite decades of research\, no existing model consistently predict
 s even simple choices\, such as selecting between lotteries. Here\, we int
 roduce BEAST Gradient Boosting (BEAST-GB)\, a novel hybrid approach that f
 uses a theory-driven behavioral model (BEAST) with state-of-the-art machin
 e learning techniques. First\, we demonstrate its success in CPC18\, an op
 en competition aimed at forecasting human choice behavior\, which BEAST-GB
  won. Second\, we show that…
DTSTART;TZID=America/Vancouver:20241216T160000
DTEND;TZID=America/Vancouver:20241216T170000
LAST-MODIFIED:20241211T000712Z
LOCATION:UBC Vancouver Campus\, ICCS X836
SUMMARY:Predicting human decisions with behavioral theories and machine lea
 rning - Ori Plonsky\, Assistant Professor\, Technion-Israel Institute of T
 echnology
TRANSP:OPAQUE
URL:https://caida.ubc.ca/event/predicting-human-decisions-behavioral-theori
 es-and-machine-learning-ori-plonsky-assistant
END:VEVENT
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