On Lower and Upper Bounds in Smooth Strongly Convex Optimization - A Unified Approach via Linear Iterative Methods.
Yossi ArjevaniPublished in: CoRR (2014)
Keyphrases
- convex optimization
- lower and upper bounds
- iterative methods
- conjugate gradient method
- lower bound
- upper bound
- operator splitting
- low rank
- interior point methods
- low rank matrix
- constrained optimization
- inverse problems
- convex programming
- total variation
- computationally expensive
- primal dual
- piecewise constant
- convex relaxation
- regularization methods
- convex optimization problems
- neural model
- augmented lagrangian
- particle swarm optimization
- np hard
- image processing