Abstract: Collaborative filtering (CF) is a widely used technique in recommender systems by automatically predicting the user’s latent interests based on many users’ historical rating data. To improve ...

Dr Zhongtian Sun is a Lecturer in the School of Computing at the University of Kent, specialising in Artificial Intelligence (AI) and Machine Learning (ML). Dr Sun is Mila Quebec AI Institute AI ...

Abstract: High-dimensional and sparse (HiDS) matrices are the basic inputs of recommender systems. Recently, autoencoder-based approaches to analyzing HiDS matrices from recommender systems are ...

The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in unsupervised ...

State-of-the-art recommender systems produce high-quality recommendations to support users in finding relevant content. However, through the utilization of users' data for generating recommendations, ...

The growing use of Recommender Systems (RS) across various industries, including e-commerce, social media, news, travel, and tourism, has prompted researchers to examine these systems for any biases ...

This is not an official NVIDIA product. It is a research project described in: "Training Deep AutoEncoders for Collaborative Filtering"(https://arxiv.org/abs/1708.01715) ...

Center for Nanophase Materials Sciences and Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States ...