Documentdetail
ID kaart
oai:arXiv.org:2408.12392
Onderwerp
Computer Science - Information Ret...Auteur
Czapp, Ádám Tibor Jani, Mátyás Domián, Bálint Hidasi, BalázsCategorie
Computer Science
Jaar
2024
vermelding datum
28-08-2024
Beschrijving
Coupling latent diffusion based image generation with contextual bandits enables the creation of eye-catching personalized product images at scale that was previously either impossible or too expensive.
In this paper we showcase how we utilized these technologies to increase user engagement with recommendations in online retargeting campaigns for e-commerce.
;Comment: Appearing in the Proceedings of the 18th ACM Conference on Recommender Systems (RecSys'24) as an Industry Track paper
Czapp, Ádám Tibor,Jani, Mátyás,Domián, Bálint,Hidasi, Balázs, 2024, Dynamic Product Image Generation and Recommendation at Scale for Personalized E-commerce
VertiSelector: Automatic Curriculum Learning for Wheeled Mobility on Vertically Challenging Terrain
sampling training learning vs
Comparison between Dual-Energy CT and Quantitative Susceptibility Mapping in Assessing Brain Iron Deposition in Parkinson Disease
nigra substantia healthy depositions p < 05 nucleus brain susceptibility ct bilateral dual-energy iron quantitative mapping values magnetic globus pallidus
