An efficient agnostic learner for halfspaces over subgaussian isotropic log-concave distributions returns a classifier with error opt+O(ε) and boundary volume O(r+ε) in time d^{~O(1/ε^2)}.
On robustness to adversarial examples and polynomial optimization
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DS 1years
2025 1verdicts
ACCEPT 1representative citing papers
citing papers explorer
-
Robust learning of halfspaces under log-concave marginals
An efficient agnostic learner for halfspaces over subgaussian isotropic log-concave distributions returns a classifier with error opt+O(ε) and boundary volume O(r+ε) in time d^{~O(1/ε^2)}.