7 citations · 25 across the 11 of their papers we have counts for
11 papers
C-XGBoost: A tree boosting model for causal effect estimation
Niki Kiriakidou, Ioannis E. Livieris, Christos Diou
Causal effect estimation aims at estimating the Average Treatment Effect as well as the Conditional Average Treatment Effect of a treatment to an outcome from the available data. T…
FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data
Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez +44
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must…
Regionally Additive Models: Explainable-by-design models minimizing feature interactions
Vasilis Gkolemis, Anargiros Tzerefos, Theodore Dalamagas +2
Generalized Additive Models (GAMs) are widely used explainable-by-design models in various applications. GAMs assume that the output can be represented as a sum of univariate funct…
RHALE: Robust and Heterogeneity-aware Accumulated Local Effects
Vasilis Gkolemis, Theodore Dalamagas, Eirini Ntoutsi +1
Accumulated Local Effects (ALE) is a widely-used explainability method for isolating the average effect of a feature on the output, because it handles cases with correlated feature…
Detection of Anomalies in Multivariate Time Series Using Ensemble Techniques
Anastasios Iliopoulos, John Violos, Christos Diou +1
Anomaly Detection in multivariate time series is a major problem in many fields. Due to their nature, anomalies sparsely occur in real data, thus making the task of anomaly detecti…
Towards Fair Face Verification: An In-depth Analysis of Demographic Biases
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos +1
Deep learning-based person identification and verification systems have remarkably improved in terms of accuracy in recent years; however, such systems, including widely popular cl…