Name
Abstract | ||
|---|---|---|
In this age of data abundance, there is a growing need for algorithms and techniques for clustering big data in an accurate and efficient manner. Well-known clustering methods of the past are computationally expensive, especially when employed to cluster massive datasets into a relatively large number of groups. The particular task of clustering millions (billions) of data points into thousands (millions) of clusters is referred to as extreme clustering. We have devised a distributed method, capable of being powered by a quantum processor, to tackle this clustering problem. |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Learning | Journal |
Volume | Citations | PageRank |
abs/1903.08256 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tim Jaschek | 1 | 0 | 0.34 |
| Jaspreet S. Oberoi | 2 | 2 | 0.74 |