Block Coordinate Descent for Regularized Multi-convex Optimization
This thesis considers regularized block multi-convex optimization, where the feasible set and objective function are generally non-convex but convex in each block of variables. I review some of its interesting examples and propose a generalized block coordinate descent (BCD) method. The generalize...
Main Author: | Xu, Yangyang |
---|---|
Other Authors: | Yin, Wotao |
Format: | Others |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | http://hdl.handle.net/1911/72066 |
Similar Items
-
Nonnegative Tensor Completion via Low-Rank Tucker Decomposition: Model and Algorithm
by: Bilian Chen, et al.
Published: (2019-01-01) -
Inégalités de Kurdyka-Lojasiewicz et convexité : algorithmes et applications
by: Nguyen, Trong Phong
Published: (2017) -
Some Applications of Eigenvalue Problems for Tensor and Tensor–Block Matrices for Mathematical Modeling of Micropolar Thin Bodies
by: Mikhail Nikabadze, et al.
Published: (2019-03-01) -
On Determination of Wave Velocities through the
Eigenvalues of Material Objects
by: Mikhail U. Nikabadze, et al.
Published: (2019-04-01) -
Optimal decay estimates for solutions to damped second order ODE's
by: Tomáš Bárta
Published: (2018-06-01)