BEGIN:VCALENDAR VERSION:2.0 PRODID:-//https://caida.ubc.ca//NONSGML iCalcreator 2.41.92// CALSCALE:GREGORIAN METHOD:PUBLISH UID:31656463-3262-4964-b038-666331336365 X-WR-RELCALID:efc09d74-9c93-479e-a94f-485231ddccde X-WR-TIMEZONE:America/Vancouver X-WR-CALNAME:Ensembles in the Age of Overparameterization: Promises and Pat hologies - Geoff Pleiss\, Assistant Professor\, UBC BEGIN:VTIMEZONE TZID:America/Vancouver TZUNTIL:20261101T090000Z BEGIN:STANDARD TZNAME:PST DTSTART:20231105T020000 TZOFFSETFROM:-0700 TZOFFSETTO:-0800 RDATE:20241103T020000 RDATE:20251102T020000 END:STANDARD BEGIN:DAYLIGHT TZNAME:PDT DTSTART:20240310T020000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 RDATE:20250309T020000 RDATE:20260308T020000 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:d192f8e9-fc7f-43b2-9414-a3c22e89d7da DTSTAMP:20260306T065842Z CLASS:PUBLIC CREATED:20241016T225047Z DESCRIPTION:Zoom Link Abstract: Ensemble methods have historically used eit her high-bias base learners (e.g. through boosting) or high-variance base learners (e.g. through bagging). Modern neural networks cannot be understo od through this classic bias-variance tradeoff\, yet 'deep ensembles' are pervasive in safety-critical and high-uncertainty application domains. Thi s talk will cover surprising and counterintuitive phenomena that emerge wh en ensembling overparameterized base models like neural networks. While de ep ensembles improve generalization in a simple and cost-effective manner\ , their accuracy and… DTSTART;TZID=America/Vancouver:20241023T110000 DTEND;TZID=America/Vancouver:20241023T120000 LAST-MODIFIED:20241017T211532Z LOCATION:UBC Vancouver Campus\, ICCS X836 / Please register to receive Zoom link SUMMARY:Ensembles in the Age of Overparameterization: Promises and Patholog ies - Geoff Pleiss\, Assistant Professor\, UBC TRANSP:OPAQUE URL:https://caida.ubc.ca/index.php/event/ensembles-age-overparameterization -promises-and-pathologies-geoff-pleiss-assistant-professor END:VEVENT END:VCALENDAR