Title :
A Deep Connection Between the Vapnik–Chervonenkis Entropy and the Rademacher Complexity
Author :
Anguita, Davide ; Ghio, Alessandro ; Oneto, Luca ; Ridella, Sandro
Author_Institution :
Dept. of Electr., Electron., Telecommun. Eng., & Naval Archit., Univ. of Genova, Genoa, Italy
Abstract :
In this paper, we derive a deep connection between the Vapnik-Chervonenkis (VC) entropy and the Rademacher complexity. For this purpose, we first refine some previously known relationships between the two notions of complexity and then derive new results, which allow computing an admissible range for the Rademacher complexity, given a value of the VC-entropy, and vice versa. The approach adopted in this paper is new and relies on the careful analysis of the combinatorial nature of the problem. The obtained results improve the state of the art on this research topic.
Keywords :
computational complexity; entropy; Rademacher complexity; Vapnik-Chervonenkis entropy; complexity notion; Annealing; Complexity theory; Entropy; Hamming distance; Learning systems; Statistical learning; Upper bound; Complexity measures; Rademacher complexity; Vapnik-Chervonenkis (VC) entropy.; Vapnik???Chervonenkis (VC) entropy; statistical learning theory;
Journal_Title :
Neural Networks and Learning Systems, IEEE Transactions on
DOI :
10.1109/TNNLS.2014.2307359