Tight Variational Bounds via Random Projections and I-Projections.
Lun-Kai HsuTudor AchimStefano ErmonPublished in: AISTATS (2016)
Keyphrases
- random projections
- lower bound
- upper bound
- worst case
- dimensionality reduction
- compressive sensing
- dimension reduction
- compressed sensing
- sparse representation
- image reconstruction
- original data
- random sampling
- image segmentation
- principal component analysis
- low dimensional
- high dimensionality
- optical flow
- np hard
- optimal solution
- document clustering
- face recognition
- data sets
- high dimensional
- machine learning
- objective function
- data analysis
- feature space
- active learning