2 papers
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…
stat.ML2024
Rejection via Learning Density Ratios
Alexander Soen, Hisham Husain, Philip Schulz +1
Classification with rejection emerges as a learning paradigm which allows models to abstain from making predictions. The predominant approach is to alter the supervised learning pi…