244 citations · 264 across the 2 of their papers we have counts for
3 papers
cs.CV2020★ 244 cited
Infinite Feature Selection: A Graph-based Feature Filtering Approach
Giorgio Roffo, Simone Melzi, Umberto Castellani +2
We propose a filtering feature selection framework that considers subsets of features as paths in a graph, where a node is a feature and an edge indicates pairwise (customizable) r…
cs.CV2017
Infinite Latent Feature Selection: A Probabilistic Latent Graph-Based Ranking Approach
Giorgio Roffo, Simone Melzi, Umberto Castellani +1
Feature selection is playing an increasingly significant role with respect to many computer vision applications spanning from object recognition to visual object tracking. However,…
cs.CV2017★ 20 cited
Ranking to Learn and Learning to Rank: On the Role of Ranking in Pattern Recognition Applications
Giorgio Roffo
The last decade has seen a revolution in the theory and application of machine learning and pattern recognition. Through these advancements, variable ranking has emerged as an acti…