Spencer Frei
where else to find them
what they talk about
where they keep going back
no series more than once — all 3 in the filters
on a stage with
never shared a talk
who talks about the same things
nobody close enough yet
| title | conference | date |
|---|---|---|
| Tutorial: Statistical Learning Theory and Neural Networks I | Deep Learning Theory Workshop and Summer School 2022 | 2022-08-01 |
Review of uniform laws of large numbers and concrete complexity tools: VC dimension (upper bound ≈ O(P·L) for ReLU nets) and Rademacher complexity, with a… | ||
| Tutorial: Statistical Learning Theory and Neural Networks II | Deep Learning Theory Workshop and Summer School 2022 | 2022-08-01 |
Shows that gradient-based training either satisfies a Polyak–Lojasiewicz (PL) inequality (so stationary points imply small empirical exponential loss) under… | ||
| Self-Training Converts Weak Learners to Strong Learners in Mixture Models | Deep Learning Theory Symposium 2021 | 2021-12-03 |
Shows that self-training with pseudo-labelers turns a classifier that has constant error below a fixed C_error constant into one within ε of the Bayes optimal… | ||
| Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent | Meet the Fellows Welcome Event | 2021-09-08 |
Defines proxy convexity: two auxiliary functions h and g that sandwich a nonconvex objective so first-order guarantees transfer. Proves a proxy PL inequality… | ||
| nothing matches | ||