加入
Deep learning versus linear models across all input distributions
Decide whether classes that SGD on ReLU networks learns under every input distribution always have small dimension complexity.
+18 −0 scienceslack.json 新增 查看文件
| @@ -0,0 +1,18 @@ | ||
| 1 | +{ | |
| 2 | + "domain": "computer-science", | |
| 3 | + "topics": [ | |
| 4 | + "learning-theory" | |
| 5 | + ], | |
| 6 | + "type": "proof", | |
| 7 | + "source": { | |
| 8 | + "key": "colt", | |
| 9 | + "name": "COLT open problems", | |
| 10 | + "url": "https://proceedings.mlr.press/v336/feldman26a.html", | |
| 11 | + "id": "v336/feldman26a", | |
| 12 | + "curator": "Conference on Learning Theory (COLT)", | |
| 13 | + "poser": "Vitaly Feldman, Pritish Kamath and Nathan Srebro", | |
| 14 | + "status": "open", | |
| 15 | + "as_of": "2026-10-20", | |
| 16 | + "catalog": "0521c19bbd38" | |
| 17 | + } | |
| 18 | +} | |