An Optimal Algorithm for Bandit Convex Optimization with Strongly-Convex and Smooth Loss.
Shinji ItoPublished in: AISTATS (2020)
Keyphrases
- convex optimization
- primal dual
- dynamic programming
- worst case
- globally optimal
- objective function
- convex relaxation
- computational complexity
- convex constraints
- hinge loss
- convex formulation
- optimal solution
- interior point methods
- convex programming
- cost function
- dual formulation
- learning algorithm
- augmented lagrangian
- norm minimization
- convex hull
- np hard
- alternating direction method of multipliers
- quadratic program
- multiresolution
- augmented lagrangian method