Name
Abstract | ||
|---|---|---|
We report and compare the performance of different learning algorithms based on data from cortical recordings. The task is to predict the orientation of visual stimuli from the activity of a population of simultaneously recorded neurons. We compare several ways of improving the coding of the input (i.e., the spike data) as well as of the output (i.e., the orientation), and report the results obtained using different kernel algorithms. |
Year | Venue | Field |
|---|---|---|
2003 | ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 16 | Kernel (linear algebra),Population,Pattern recognition,Computer science,Algorithm,Coding (social sciences),Artificial intelligence,Machine learning,Visual perception |
DocType | Volume | ISSN |
Conference | 16 | 1049-5258 |
Citations | PageRank | References |
11 | 1.11 | 4 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jan Eichhorn | 1 | 227 | 26.87 |
| a s tolias | 2 | 87 | 10.70 |
| Alexander Zien | 3 | 1255 | 146.93 |
| Malte Kuss | 4 | 134 | 16.24 |
| carl edward rasmussen | 5 | 2628 | 309.77 |
| Jason Weston | 6 | 13068 | 805.30 |
| Nikos Logothetis | 7 | 77 | 5.60 |
| Bernhard Schölkopf | 8 | 23120 | 3091.82 |