Timeline for Applications of algebraic geometry to machine learning
Current License: CC BY-SA 3.0
4 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Mar 14, 2017 at 2:57 | comment | added | Henry.L | The same problem also occur in some of Sturmfel's students' works, they seem to use tropical geometry as an optimization tool instead of an explanatory framework when it comes to real data. Maybe I am wrong, but what I think AG should provide is a theoretical framework underlying the data... | |
| Mar 14, 2017 at 2:54 | comment | added | Henry.L | ...and the reason is simply that higher order topological structures have not so far been found to be relevant to practical inference / classification problems. Persistence cohomology is quite a thing at the first glance in cosmology as well as neural data due to its scaling-resistant. But the more I delved into it I agree with your comment more that it just formally involve in the data. | |
| Mar 23, 2016 at 15:55 | vote | accept | Lisp Rambo | ||
| Mar 20, 2016 at 12:24 | history | answered | Paul Siegel | CC BY-SA 3.0 |