We have 4 of 10 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
While WPOs can substantially reduce the cost of individual oracle calls, this comes with an inherent loss in oracle complexity, so a new upper-bound is provided for WPO-based nonsmooth convex composite optimization, nearly matching the proximal subgradient method.
A method is introduced whose number of iterations to reach an $\epsilon$-approximate solution is of the order of n, and whose number of iterations to $\epsilon$-approximation scales with $\frac{\beta{}D^2n}{\alpha}\log(1/\epsilon)$, in a meaningful regime.
We develop new accelerated first-order algorithms in the Frank-Wolfe (FW) family for minimizing smooth convex functions over compact convex sets, with a focus on two prominent constraint classes: (1) polytopes and (2) matrix domains given by the spectrahedron and nuclear-norm balls. A key technical ingredient is a comp...
This work gives a deterministic and parameter-free Frank-Wolfe-type method with a global ambient-dimension-independent linear convergence rate under quadratic growth.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
