Abstract
This paper proposes a supervised and fully-distributed intelligent classification algorithm that is accurate and scalable for large networks. In addition, the resulting algorithm has the following interesting features: fully-distributed, asynchronous, light-weight, online learning, and fast responses. These characteristics make it scalable for large networks. A major distinction of our method compared to the other approaches is that it forms a single global classifier, instead of building many local classifiers (one at every site). Fine-granularity components of the classifier are distributed across the network by using Distributed Hash Table (DHT) --- which provides efficient linking to these components and ensures the system remains fully-distributed. Our simulation results also show that the proposed method is more communication-efficient than several other distributed algorithms. The results also show that the distributed algorithm is able to produce accurate results that are comparable to the available state-of-the-art machine learning techniques.
Original language | English |
---|---|
Title of host publication | Proceedings of the Fifth Symposium on Information and Communication Technology (SoICT 2015) |
Editors | Luc De Raedt, Yves Deville, Marc Bui, Dieu Linh Truong |
Place of Publication | New York NY USA |
Publisher | Association for Computing Machinery (ACM) |
Pages | 75-82 |
Number of pages | 8 |
ISBN (Print) | 9781450338431 |
DOIs | |
Publication status | Published - 2015 |
Event | International Symposium on Information and Communication Technology 2015 - Hue, Vietnam Duration: 3 Jan 2015 → 4 Dec 2015 Conference number: 6th https://dl.acm.org/doi/proceedings/10.1145/2833258 |
Conference
Conference | International Symposium on Information and Communication Technology 2015 |
---|---|
Abbreviated title | SoICT 2015 |
Country/Territory | Vietnam |
City | Hue |
Period | 3/01/15 → 4/12/15 |
Internet address |