How can user feedback on explanations be used to improve both the explanations themselves and the underlying recommendation models?

Mar 29, 2022 ... Tutorial: Reinforcement learning for recommender systems ... Hands-on tutorial on RL and RLlib for building recommendation systems. In this 2-hour ... Nov 20, 2021 ... Abstract. Deep learning has profoundly impacted many areas of machine learning. However, it took a while for its impact to be felt in the field ... Jun 17, 2020 ... Recommender System with Machine Learning and Artificial Intelligence: Practical Tools and Applications in Medical, Agricultural and Other ... Oct 13, 2022 ... Chemical compositions registered in the inorganic crystal structure database (ICSD) were supplied to machine learning for binary classification. ApplyingML · Reinforcement Learning for Recommendation Systems · Contextual bandits: Multi-armed bandits with context · Value-based: Learning value for each ... Apr 22, 2025 ... Recommendation engines in this category rely on machine learning algorithms, such as clustering models, regression, user-based k-nearest ... Apr 19, 2021 ... I developed a game recommendation system model. It was an extremely complex development for me, as I am still gaining experience and knowledge in Machine ... Aug 15, 2022 ... This writeup is about using reinforcement learning to construct an optimal list of recommendations when the user has a finite time budget to make a decision. Jul 11, 2024 ... Today's recommender systems from leading companies like Amazon, Google, Rakuten, TikTok, and others are highly sophisticated models powered by ... Mar 28, 2025 ... Recommendation systems use data-driven methodologies to provide users with tailored suggestions. These systems utilize user data and ...