3 papers
cs.LG2026
On the Mechanisms of Collaborative Learning in VAE Recommenders
Tung-Long Vuong, Julien Monteil, Hien Dang +3
Variational Autoencoders (VAEs) are a powerful alternative to matrix factorization for recommendation. A common technique in VAE-based collaborative filtering (CF) consists in appl…
cs.IR2024
MARec: Metadata Alignment for cold-start Recommendation
Julien Monteil, Volodymyr Vaskovych, Wentao Lu +2
For many recommender systems, the primary data source is a historical record of user clicks. The associated click matrix is often very sparse, as the number of users x products can…
eess.SY2024
Personalised Outfit Recommendation via History-aware Transformers
Myong Chol Jung, Julien Monteil, Philip Schulz +1
We present the history-aware transformer (HAT), a transformer-based model that uses shoppers' purchase history to personalise outfit predictions. The aim of this work is to recomme…