Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits.
Huasen WuR. SrikantXin LiuChong JiangPublished in: NIPS (2015)
Keyphrases
- worst case
- regret bounds
- learning algorithm
- benchmark datasets
- lower bound
- orders of magnitude
- online convex optimization
- data structure
- computational complexity
- bandit problems
- loss function
- multi armed bandits
- regret minimization
- expert advice
- convergence analysis
- online algorithms
- convergence rate
- computational efficiency
- neural network
- online learning
- multi class
- upper bound
- image segmentation
- genetic algorithm