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Transformers4Rec: Bridging the Gap between NLP and Sequential / Session-Based Recommendation.

, , , , and . RecSys, page 143-153. ACM, (2021)

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Transformers with multi-modal features and post-fusion context for e-commerce session-based recommendation., , , , and . CoRR, (2021)Temporal deep learning framework for retinopathy prediction in patients with type 1 diabetes., , , , , , , and . Artif. Intell. Medicine, (2022)Optimized deep learning-based multimodal method for irregular medical timestamped data. (Méthode multimodale optimisée basée sur l'apprentissage profond pour les données médicales temporelles irrégulières).. Polytechnic Institute of Paris, Palaiseau, France, (2022)LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking., , , , and . CoRR, (2023)Training and Deploying Multi-Stage Recommender Systems., , , and . RecSys, page 706-707. ACM, (2022)Accelerating recommender system training 15x with RAPIDS., , , , , and . RecSys Challenge, page 8:1-8:5. ACM, (2019)Synthetic Data and Simulators for Recommendation Systems: Current State and Future Directions., , , and . CoRR, (2021)End-to-End Session-Based Recommendation on GPU., , , and . RecSys, page 831-833. ACM, (2021)Building and Deploying a Multi-Stage Recommender System with Merlin., , , , and . RecSys, page 632-635. ACM, (2022)Reducing the Friction for Building Recommender Systems with Merlin., , , , and . KDD, page 4816-4817. ACM, (2022)