145 citations · 456 across the 34 of their papers we have counts for
4 papers · 1 filter
Personalized Recommender Systems for Gym Workouts: A Reinforcement Learning Approach
Roan Rosema, Helma Torkamaan, Masoud Mansoury
Workout recommender systems aim to help gym users complete effective and engaging training sessions. However, recommending exercises alone is insufficient, as a practical system mu…
From Top-1 to Top-K: A Reproducibility Study and Benchmarking of Counterfactual Explanations for Recommender Systems
Quang-Huy Nguyen, Thanh-Hai Nguyen, Khac-Manh Thai +6
Counterfactual explanations (CEs) provide an intuitive way to understand recommender systems by identifying minimal modifications to user-item interactions that alter recommendatio…
From Insight to Intervention: Interpretable Neuron Steering for Controlling Popularity Bias in Recommender Systems
Parviz Ahmadov, Masoud Mansoury
Popularity bias is a pervasive challenge in recommender systems, where a few popular items dominate attention while the majority of less popular items remain underexposed. This imb…
The Unfairness of Multifactorial Bias in Recommendation
Masoud Mansoury, Jin Huang, Mykola Pechenizkiy +2
Popularity bias and positivity bias are two prominent sources of bias in recommender systems. Both arise from input data, propagate through recommendation models, and lead to unfai…