VisRec: A Hands-on Tutorial on Deep Learning for Visual Recommender Systems

RL1, Publisher:, Link>


Denis Parra, Antonio Ossa-Guerra, Manuel Cartagena, Patricio Cerda-Mardini, Felipe del Rio


This tutorial serves as an introduction to deep learning approaches to build visual recommendation systems. Deep learning models can be used as feature extractors, and perform extremely well in visual recommender systems to create representations of visual items. This tutorial covers the foundations of convolutional neural networks and then how to use them to build state-of-the-art personalized recommendation systems. The tutorial is designed as a hands-on experience, focused on providing both theoretical knowledge as well as practical experience on the topics of the course.

0 visualizaciones

Entradas Recientes

Ver todo

RL2, Publisher: Journal of Machine Learning Research, Link> AUTHORS Jorge Pérez, Pablo Barceló, Javier Marinkovic ABSTRACT Alternatives to recurrent neural networks, in particular, architectures bas

RL2, Publisher: https://github.com/pdm-book/community Link> AUTHORS Marcelo Arenas, Pablo Barceló, Leonid Libkin, Wim Martens, Andreas Pieris ABSTRACT This is a release of parts 1, 2, and 4 of the