On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives.
Aaditya RamdasSashank J. ReddiBarnabás PóczosAarti SinghLarry A. WassermanPublished in: CoRR (2014)
Keyphrases
- high dimensional
- kernel function
- feature space
- kernel space
- small sample
- input space
- low dimensional
- additive models
- power consumption
- test data
- similarity search
- high dimensional data
- worst case
- data points
- dimensionality reduction
- test cases
- kernel methods
- high dimensionality
- kernel matrix
- nearest neighbor
- kernel principal component analysis
- high dimensional feature space
- kernel regression
- high dimensional problems
- sparse data
- software testing
- multi dimensional
- feature extraction
- support vector
- linear combination
- reproducing kernel hilbert space
- variable selection
- sparse coding
- parameter space
- gene expression data
- machine learning
- decision makers