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UID:20260624T013442EDT-7424ni0Vbb@132.216.98.100
DTSTAMP:20260624T053442Z
DESCRIPTION:Speaker: Niloofar Tarighat (supervised by Maxime Cohen and Jame
 s Clark)\n\nAlthough many approaches have been developed to accurately pre
 dict the demand of products based on their historical sales data\, demand 
 prediction is still a complex issue especially when there is a domain shif
 t between training and testing data. In this work\, we study three example
 s of domain shifts in the context of retail: outbreak of the COVID-19 pand
 emic\, opening a new store\, and introducing a new product.\n\nThis talk i
 s one of a series of three exciting presentations given by graduate studen
 ts as part of their research work at the retail innovation lab\, in partne
 rship with Couche-Tard. They will be presenting an overview of their resea
 rch projects\, study objectives\, challenges faced\, results\, and their r
 eal-world application in retail. Representatives of the relevant business 
 units from Couche-Tard will also be present.\n
DTSTART:20221216T150000Z
DTEND:20221216T160000Z
LOCATION:CA\, ZOOM
SUMMARY:Domain Adaptation for Demand Prediction in Retail
URL:/cim/channels/event/domain-adaptation-demand-predi
 ction-retail-351876
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