Binary domain generalization for sparsifying binary neural networks ⋆ - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

Binary domain generalization for sparsifying binary neural networks ⋆

Francesco Galati
  • Fonction : Auteur
  • PersonId : 1128335
Maria A. Zuluaga

Résumé

Binary neural networks (BNNs) are an attractive solution for developing and deploying deep neural network (DNN)-based applications in resource constrained devices. Despite their success, BNNs still suffer from a fixed and limited compression factor that may be explained by the fact that existing pruning methods for full-precision DNNs cannot be directly applied to BNNs. In fact, weight pruning of BNNs leads to performance degradation, which suggests that the standard binarization domain of BNNs is not well adapted for the task. This work proposes a novel more general binary domain that extends the standard binary one that is more robust to pruning techniques, thus guaranteeing improved compression and avoiding severe performance losses. We demonstrate a closed-form solution for quantizing the weights of a full-precision network into the proposed binary domain. Finally, we show the flexibility of our method, which can be combined with other pruning strategies. Experiments over CIFAR-10 and CIFAR-100 demonstrate that the novel approach is able to generate efficient sparse networks with reduced memory usage and run-time latency, while maintaining performance.
Fichier principal
Vignette du fichier
ECML_PKDD.pdf (512.43 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04139453 , version 1 (23-06-2023)

Identifiants

Citer

Riccardo Schiavone, Francesco Galati, Maria A. Zuluaga. Binary domain generalization for sparsifying binary neural networks ⋆. ECML-PKDD 2023, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Springer, Sep 2023, Torino, Italy. ⟨hal-04139453⟩
36 Consultations
18 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More