You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
Chapter title |
Decentralized Recommendation Based on Matrix Factorization: A Comparison of Gossip and Federated Learning
|
---|---|
Chapter number | 27 |
Book title |
Machine Learning and Knowledge Discovery in Databases
|
Published by |
Springer, Cham, September 2019
|
DOI | 10.1007/978-3-030-43823-4_27 |
Book ISBNs |
978-3-03-043822-7, 978-3-03-043823-4
|
Authors |
István Hegedűs, Gábor Danner, Márk Jelasity, Hegedűs, István, Danner, Gábor, Jelasity, Márk |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 38 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 7 | 18% |
Student > Master | 4 | 11% |
Researcher | 3 | 8% |
Student > Doctoral Student | 2 | 5% |
Professor > Associate Professor | 2 | 5% |
Other | 3 | 8% |
Unknown | 17 | 45% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 14 | 37% |
Engineering | 4 | 11% |
Decision Sciences | 1 | 3% |
Unknown | 19 | 50% |