On the uniform concentration bounds and large sample properties of clustering with Bregman divergences
From MaRDI portal
Publication:6541771
DOI10.1002/sta4.360MaRDI QIDQ6541771
Debolina Paul, Saptarshi Chakraborty, Swagatam Das
Publication date: 21 May 2024
Published in: Stat (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Strong consistency of \(k\)-parameters clustering
- Strong consistency of k-means clustering
- A central limit theorem for k-means clustering
- A simple approach to sparse clustering
- Regularized \(k\)-means clustering of high-dimensional data and its asymptotic consistency
- Robust and sparse \(k\)-means clustering for high-dimensional data
- Strong consistency of factorial \(k\)-means clustering
- A survey of kernel and spectral methods for clustering
- Strong Consistency of ReducedK-means Clustering
- Robust Clustering Using Outlier-Sparsity Regularization
- Least squares quantization in PCM
- On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
- On the strong consistency of feature-weighted \(k\)-means clustering in a nearmetric space
Related Items (1)
This page was built for publication: On the uniform concentration bounds and large sample properties of clustering with Bregman divergences