Wird geladen...
Computational Information Geometry for Binary Classification of High-Dimensional Random Tensors †
Evaluating the performance of Bayesian classification in a high-dimensional random tensor is a fundamental problem, usually difficult and under-studied. In this work, we consider two Signal to Noise Ratio (SNR)-based binary classification problems of interest. Under the alternative hypothesis, i.e.,...
Gespeichert in:
| Veröffentlicht in: | Entropy (Basel) |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
MDPI
2018
|
| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7512719/ https://ncbi.nlm.nih.gov/pubmed/33265294 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e20030203 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|