Name
Abstract | ||
|---|---|---|
Associative memories are data structures that allow retrieval of stored messages from part of their content. They thus behave similarly to human brain that is capable for instance of retrieving the end of a song given its beginning. Among different families of associative memories, sparse ones are known to provide the best efficiency (ratio of the number of bits stored to that of bits used). Nevertheless, it is well known that non-uniformity of the stored messages can lead to dramatic decrease in performance. We introduce several strategies to allow efficient storage of non-uniform messages in recently introduced sparse associative memories. We analyse and discuss the methods introduced. We also present a practical application example. |
Year | Venue | Field |
|---|---|---|
2013 | arXiv: Neural and Evolutionary Computing | Data structure,Associative property,Computer science,Theoretical computer science |
DocType | Volume | Citations |
Journal | abs/1307.6410 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bartosz Boguslawski | 1 | 6 | 1.49 |
| Vincent Gripon | 2 | 210 | 27.16 |
| Fabrice Seguin | 3 | 36 | 16.02 |
| Frédéric Heitzmann | 4 | 10 | 1.94 |