Name
Abstract | ||
|---|---|---|
This talk covers techniques for analyzing data sets with up to trillions of examples with billions of features, using thousands of computers. To operate at this scale requires an understanding of an increasing complex hardware hierarchy (e.g. cache, memory, SSD, another machine in the rack, disk, a machine in another data center, ...); a model for recovering from inevitable hardware and software failures; a machine learning model that allows for efficient computation over large, continuously updated data sets; and a way to visualize and share the results. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2020408.2020412 | KDD |
Keywords | Field | DocType |
internet scale data analysis,data center,updated data set,inevitable hardware,software failure,efficient computation,complex hardware hierarchy,data analysis,machine learning,cache memory | Data mining,Data set,Computer science,Cache,Data diffusion machine,Software,Artificial intelligence,Hierarchy,Data center,Machine learning,Computation,The Internet | Conference |
Citations | PageRank | References |
1 | 0.41 | 0 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter Norvig | 1 | 425 | 61.47 |