How can group recommendations be generated using collaborative filtering?

Collaborative filtering; deep learning; generative adversarial networks; recommender systems. Issue Date: 2019-03. Publisher: IEEE-INST ELECTRICAL ELECTRONICS ... May 16, 2013 ... I am mostly interested in collaborative filtering, so I started with the example on finding recomendations from the BookCrossing dataset. I ... Proceedings of the Ninth Asian Conference on Machine Learning, PMLR 77:224-239, 2017. Abstract. Collaborative Filtering (CF), a well-known approach in ... Collaborative filtering is a technique that can filter out items that a user might like on the basis of reactions by similar users. Jun 5, 2014 ... Like most machine learning algorithms, the most important input that a collaborative filtering algorithm needs is data -- lots of it. So if you ... Aug 9, 2018 ... Algorithm selection and hyperparameter tuning remain two of the most challenging tasks in machine learning. Automated machine learning ... Hinton, “Restricted Boltzmann Machines for Collaborative Filtering”, 24th International Conference on Machine Learning, 2007, 791–798. X. He, L. Liao, H ... In this paper we introduce SVDFeature, a machine learning toolkit for feature-based collaborative filtering. SVDFeature is designed to efficiently solve the ... Collaborative Filtering: Using Machine Learning and Statistical Techniques · Other sellers on AmazonOther sellers on Amazon · Book details. Print length. 164 ... Carreira-Perpinan, M., & Hinton, G. (2005). On contrastive divergence learning. 10th Int. Work-shop on Artificial Intelligence and Statistics (AISTATS'2005).