7 citations · 11 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 4 cited
Feature space reduction method for ultrahigh-dimensional, multiclass data: Random forest-based multiround screening (RFMS)
Gergely Hanczár, Marcell Stippinger, Dávid Hanák +4
In recent years, numerous screening methods have been published for ultrahigh-dimensional data that contain hundreds of thousands of features; however, most of these features canno…
cs.LG2022★ 7 cited
BiometricBlender: Ultra-high dimensional, multi-class synthetic data generator to imitate biometric feature space
Marcell Stippinger, Dávid Hanák, Marcell T. Kurbucz +3
The lack of freely available (real-life or synthetic) high or ultra-high dimensional, multi-class datasets may hamper the rapidly growing research on feature screening, especially…