Jose Perea (Northeastern U)
Approximate vector bundles
Many data science tasks—like dimensionality reduction or synchronization problems—can be phrased in terms of bundle-theoretic constructions. However, noise and error measurements can prevent said interpretations from being readily applicable in practice. In this talk, I will present recent work introducing notions of approximate and discrete vector bundles, along with examples of how they can be applied.