32 citations · 34 across the 4 of their papers we have counts for
5 papers
HypeRS: Building a Hypergraph-driven ensemble Recommender System
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
Recommender systems are designed to predict user preferences over collections of items. These systems process users' previous interactions to decide which items should be ranked hi…
BELLATREX: Building Explanations through a LocaLly AccuraTe Rule EXtractor
Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos +1
Tree-ensemble algorithms, such as random forest, are effective machine learning methods popular for their flexibility, high performance, and robustness to overfitting. However, sin…
Drug-Target Interaction Prediction via an Ensemble of Weighted Nearest Neighbors with Interaction Recovery
Bin Liu, Konstantinos Pliakos, Celine Vens +1
Predicting drug-target interactions (DTI) via reliable computational methods is an effective and efficient way to mitigate the enormous costs and time of the drug discovery process…
Fair Multi-Stakeholder News Recommender System with Hypergraph ranking
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
Recommender systems are typically designed to fulfill end user needs. However, in some domains the users are not the only stakeholders in the system. For instance, in a news aggreg…
Deep tree-ensembles for multi-output prediction
Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
Recently, deep neural networks have expanded the state-of-art in various scientific fields and provided solutions to long standing problems across multiple application domains. Nev…