2 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
Uncertainty-Aware Post-Hoc Calibration: Mitigating Confidently Incorrect Predictions Beyond Calibration Metrics
Hassan Gharoun, Mohammad Sadegh Khorshidi, Kasra Ranjbarigderi +2
Despite extensive research on neural network calibration, existing methods typically apply global transformations that treat all predictions uniformly, overlooking the heterogeneou…
Clustering in Dynamic Environments: A Framework for Benchmark Dataset Generation With Heterogeneous Changes
Danial Yazdani, Juergen Branke, Mohammad Sadegh Khorshidi +4
Clustering in dynamic environments is of increasing importance, with broad applications ranging from real-time data analysis and online unsupervised learning to dynamic facility lo…
Semantic-Preserving Feature Partitioning for Multi-View Ensemble Learning
Mohammad Sadegh Khorshidi, Navid Yazdanjue, Hassan Gharoun +4
In machine learning, the exponential growth of data and the associated ``curse of dimensionality'' pose significant challenges, particularly with expansive yet sparse datasets. Add…
Noise-Augmented Boruta: The Neural Network Perturbation Infusion with Boruta Feature Selection
Hassan Gharoun, Navid Yazdanjoe, Mohammad Sadegh Khorshidi +1
With the surge in data generation, both vertically (i.e., volume of data) and horizontally (i.e., dimensionality), the burden of the curse of dimensionality has become increasingly…