Model Compression by Entropy Penalized Reparameterization

By Deniz Oktay, Johannes Ballé, Saurabh Singh, Abhinav Shrivastava. 2019

5 citations recorded by the source corpus.

Subfields: Efficiency & Compression

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Efficiency & Compression

1. Medhi Bennis
2. Jakub Konecný
3. Oluwasanmi Koyejo
4. Martin Jaggi
5. Ananda Theertha Suresh
6. Qiang Yang
7. Sebastian U. Stich
8. Mehryar Mohri

Citations in the corpus

• Advances and Open Problems in Federated Learning (2019, background): “This topic has received a lot of attention in the broader ML community [194, 120, 436, 270, 312], but these methods either do not have a straightforward mapping to federated learning, or make the training process more complex which makes it difficult to adopt.”