Dantzig Selector with an Approximately Optimal Denoising Matrix and its Application in Sparse Reinforcement Learning.
Bo LiuLuwan ZhangJi LiuPublished in: UAI (2016)
Keyphrases
- approximately optimal
- denoising
- reinforcement learning
- basis pursuit
- coefficient matrix
- sparse matrix
- image denoising
- noisy images
- natural images
- mechanism design
- rank minimization
- total variation
- image processing
- high dimensional
- function approximation
- reinforcement learning algorithms
- model free
- wavelet packet
- low rank
- state space
- approximation ratio
- soft thresholding
- binary matrices
- markov decision processes
- sparse coding
- machine learning
- multi agent
- eigenvalue decomposition
- sparse representation
- tensor factorization
- low rank approximation
- compressed sensing
- denoising algorithm
- noise reduction
- low rank matrix
- tensor decomposition
- denoising methods
- least squares
- matrix factorization
- signal recovery
- learning algorithm
- temporal difference