[Seminar][NaverLabsEurope] Charlotte Laclau - ML for online advertising and recommender systems
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perez.jln
Mar 15, 2018, 4:25:36 AM3/15/18
to SMILE in Grenoble
Dear all,
Speaker: Charlotte Laclau, post-doctoral researcher at Laboratoire d'Informatique de Grenoble, Grenoble, France (hosted by Julien Perez)
Title: Project Calypso: machine learning for online advertising and recommender systems
Abstract:
Calypso is an FUI project in collaboration with the University of Grenoble Alps and two companies, Kelkoo and Purch, on recommender systems and online advertising. In this talk, I will present some of the contributions made since the beginning of the project in November 2015, including the release of two large-scale datasets extracted from both companies' online traffic and RecNet, a novel ranking framework for collaborative filtering that jointly learns a new representation of users and items in an embedded space as well as the preference relation of users over pairs of items. Finally, I will present some challenges in taking into account implicit feedback, large-scale optimization and the need for diversity on bias data.
Venue:
Naver Labs Europe, 03/15 - 11pm
Cheers,
--
Julien Perez, PhD
Lead - Machine Learning and Optimization group
Naver Labs Europe
Speaker: Charlotte Laclau, post-doctoral researcher at Laboratoire d'Informatique de Grenoble, Grenoble, France (hosted by Julien Perez)
Title: Project Calypso: machine learning for online advertising and recommender systems
Abstract:
Calypso is an FUI project in collaboration with the University of Grenoble Alps and two companies, Kelkoo and Purch, on recommender systems and online advertising. In this talk, I will present some of the contributions made since the beginning of the project in November 2015, including the release of two large-scale datasets extracted from both companies' online traffic and RecNet, a novel ranking framework for collaborative filtering that jointly learns a new representation of users and items in an embedded space as well as the preference relation of users over pairs of items. Finally, I will present some challenges in taking into account implicit feedback, large-scale optimization and the need for diversity on bias data.
Venue:
Naver Labs Europe, 03/15 - 11pm
Cheers,
--
Julien Perez, PhD
Lead - Machine Learning and Optimization group
Naver Labs Europe
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