On the optimality of kernels for high-dimensional clustering.
Leena Chennuru VankadaraDebarghya GhoshdastidarPublished in: CoRR (2019)
Keyphrases
- high dimensional
- high dimensionality
- data points
- feature space
- clustering method
- clustering algorithm
- low dimensional
- kernel function
- dimensionality reduction
- k means
- unsupervised learning
- parameter space
- high dimensional datasets
- similarity search
- high dimensional data
- high dimensional data sets
- linear combination
- nearest neighbor
- support vector
- self organizing maps
- data mining
- hierarchical clustering
- subspace clustering
- linear svm
- sparse data
- additive models
- noisy data
- spectral clustering
- dimension reduction
- kernel methods
- cluster analysis
- information theoretic
- feature extraction
- feature selection
- machine learning