Sample complexity for 1-bit compressed sensing and sparse classification.
Ankit GuptaRobert D. NowakBenjamin RechtPublished in: ISIT (2010)
Keyphrases
- compressed sensing
- sample complexity
- image reconstruction
- supervised learning
- random projections
- sparse representation
- classification accuracy
- signal recovery
- natural images
- image classification
- signal processing
- learning problems
- support vector
- feature vectors
- support vector machine
- machine learning
- compressive sampling
- theoretical analysis
- learning algorithm
- upper bound
- feature extraction
- higher order
- irrelevant features
- similarity measure
- generalization error
- sample size
- feature space
- active learning
- special case
- feature set
- training examples
- support vector machine svm
- training samples
- cross validation
- pattern recognition
- multiscale
- dimension reduction
- high dimensional
- feature selection
- text mining
- data sets