Name
Abstract | ||
|---|---|---|
Generalized Bayesian learning algorithms are increasingly popular in machine learning, due to their PAC generalization properties and flexibility. The present paper aims at providing a self-contained survey on the resulting PAC-Bayes framework and some of its main theoretical and algorithmic developments. |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Machine Learning | Journal |
Volume | Citations | PageRank |
abs/1901.05353 | 1 | 0.36 |
References | Authors | |
27 | 1 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Benjamin Guedj | 1 | 9 | 8.82 |