Name
Abstract | ||
|---|---|---|
In this paper we address the problem of performing statistical inference for large scale data sets i.e., Big Data. The volume and dimensionality of the data may be so high that it cannot be processed or stored in a single computing node. We propose a scalable, statistically robust and computationally efficient bootstrap method, compatible with distributed processing and storage systems. Bootstrap ... |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TSP.2015.2498121 | IEEE Transactions on Signal Processing |
Keywords | DocType | Volume |
Robustness,Estimation,Complexity theory,Big data,Statistical analysis,Distributed databases,Uncertainty | Journal | 64 |
Issue | ISSN | Citations |
4 | 1053-587X | 4 |
PageRank | References | Authors |
0.58 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shahab Basiri | 1 | 12 | 3.01 |
| Esa Ollila | 2 | 351 | 33.51 |
| Visa Koivunen | 3 | 1917 | 187.81 |