Reinforcement Leaning in Feature Space: Matrix Bandit, Kernels, and Regret Bound.
Lin F. YangMengdi WangPublished in: CoRR (2019)
Keyphrases
- regret bounds
- feature space
- dot product
- kernel function
- lower bound
- online learning
- linear regression
- kernel methods
- feature vectors
- feature extraction
- upper bound
- feature selection
- dimensionality reduction
- principal component analysis
- training samples
- high dimensional
- support vector
- classification accuracy
- mean shift
- reinforcement learning
- data points
- hyperplane
- training set
- covariance matrix
- pairwise
- support vector machine
- distance metric
- bregman divergences
- feature set