no code implementations • 18 Sep 2023 • Manuel Dibak, Vladimir Vlasov, Nour Karessli, Darya Dedik, Egor Malykh, Jacek Wasilewski, Ton Torres, Ana Peleteiro Ramallo
Data-driven personalization is a key practice in fashion e-commerce, improving the way businesses serve their consumers needs with more relevant content.
no code implementations • 17 Jan 2023 • Marjan Celikik, Jacek Wasilewski, Ana Peleteiro Ramallo
A large number of empirical studies on applying self-attention models in the domain of recommender systems are based on offline evaluation and metrics computed on standardized datasets.
no code implementations • 29 Nov 2022 • Marjan Celikik, Jacek Wasilewski, Sahar Mbarek, Pablo Celayes, Pierre Gagliardi, Duy Pham, Nour Karessli, Ana Peleteiro Ramallo
A large number of empirical studies on applying self-attention models in the domain of recommender systems are based on offline evaluation and metrics computed on standardized datasets, without insights on how these models perform in real life scenarios.
no code implementations • 29 Nov 2022 • Marjan Celikik, Matthias Kirmse, Timo Denk, Pierre Gagliardi, Sahar Mbarek, Duy Pham, Ana Peleteiro Ramallo
However, to date, there is no extensive comparison of the performance of the different algorithms for outfit generation and recommendation.
no code implementations • COLING (TextGraphs) 2020 • Timo I. Denk, Ana Peleteiro Ramallo
BERT is a popular language model whose main pre-training task is to fill in the blank, i. e., predicting a word that was masked out of a sentence, based on the remaining words.