Siamak Ravanbakhsh

Logarithmic sampling regret is achievable in online learning by leveraging squared confidence widths, a fundamental departure from standard regret minimization.

Overparameterization doesn't just add parameters; it warps the loss landscape geometry itself, making well-conditioned minima easier to find.