5 citations · 8 across the 4 of their papers we have counts for
5 papers
Epsilon non-Greedy: A Bandit Approach for Unbiased Recommendation via Uniform Data
S. M. F. Sani, Seyed Abbas Hosseini, Hamid R. Rabiee
Often, recommendation systems employ continuous training, leading to a self-feedback loop bias in which the system becomes biased toward its previous recommendations. Recent studie…
ChOracle: A Unified Statistical Framework for Churn Prediction
Ali Khodadadi, Seyed Abbas Hosseini, Ehsan Pajouheshgar +2
User churn is an important issue in online services that threatens the health and profitability of services. Most of the previous works on churn prediction convert the problem into…
Recurrent Poisson Factorization for Temporal Recommendation
Seyed Abbas Hosseini, Keivan Alizadeh, Ali Khodadadi +4
Poisson factorization is a probabilistic model of users and items for recommendation systems, where the so-called implicit consumer data is modeled by a factorized Poisson distribu…
Continuous-Time User Modeling in the Presence of Badges: A Probabilistic Approach
Ali Khodadadi, Seyed Abbas Hosseini, Erfan Tavakoli +1
User modeling plays an important role in delivering customized web services to the users and improving their engagement. However, most user models in the literature do not explicit…
HNP3: A Hierarchical Nonparametric Point Process for Modeling Content Diffusion over Social Media
Seyed Abbas Hosseini, Ali Khodadadi, Soheil Arabzade +1
This paper introduces a novel framework for modeling temporal events with complex longitudinal dependency that are generated by dependent sources. This framework takes advantage of…