163 citations · 724 across the 59 of their papers we have counts for
5 papers · 1 filter
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…
DANI: Fast Diffusion Aware Network Inference with Preserving Topological Structure Property
Maryam Ramezani, Aryan Ahadinia, Erfan Farhadi +1
The fast growth of social networks and their data access limitations in recent years has led to increasing difficulty in obtaining the complete topology of these networks. However,…
ClusterSeq: Enhancing Sequential Recommender Systems with Clustering based Meta-Learning
Mohammmadmahdi Maheri, Reza Abdollahzadeh, Bardia Mohammadi +3
In practical scenarios, the effectiveness of sequential recommendation systems is hindered by the user cold-start problem, which arises due to limited interactions for accurately d…
Enhancing the Prediction of Emotional Experience in Movies using Deep Neural Networks: The Significance of Audio and Language
Sogand Mehrpour Mohammadi, Meysam Gouran Orimi, Hamidreza Rabiee
Our paper focuses on making use of deep neural network models to accurately predict the range of human emotions experienced during watching movies. In this certain setup, there exi…
Network-based Control of Epidemic via Flattening the Infection Curve: High-Clustered vs. Low-Clustered Social Networks
Mohammadreza Doostmohammadian, Hamid R. Rabiee
Recent studies in network science and control have shown a meaningful relationship between the epidemic processes (e.g., COVID-19 spread) and some network properties. This paper st…