Riemannian Optimization via Frank-Wolfe Methods
Abstract We study projection-free methods for constrained Riemannian optimization. In particular, we propose a Riemannian Frank-Wolfe (RFW) method that handles constraints directly, in contrast to prior methods that rely on (potentially costly) projections. We analyze non-asymptotic convergence rate...
Main Authors: | Weber, Melanie (Author), Sra, Suvrit (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer Science and Business Media LLC,
2022-07-18T15:51:41Z.
|
Subjects: | |
Online Access: | Get fulltext |
Similar Items
-
Projection-free nonconvex stochastic optimization on Riemannian manifolds
by: Weber, Melanie, et al.
Published: (2022) -
Distributing Frank-Wolfe via map-reduce
Published: () -
New analysis and results for the Frank-Wolfe method
by: Freund, Robert Michael, et al.
Published: (2016) -
Conditional gradient methods via stochastic path-integrated differential estimator
by: Sra, Suvrit
Published: (2021) -
Modular proximal optimization for multidimensional total-variation regularization
by: Sra, Suvrit
Published: (2021)