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Found 5 papers, 0 papers with code
MCMC Louvain for Online Community Detection
We introduce a novel algorithm of community detection that maintains dynamically a community structure of a large network that evolves with time.
A Quasi-Bayesian Perspective to Online Clustering
When faced with high frequency streams of data, clustering raises theoretical and algorithmic pitfalls.
The algorithm of noisy k-means
In this note, we introduce a new algorithm to deal with finite dimensional clustering with errors in variables.
Adaptive Noisy Clustering
This selection rule is based on the Lepski's principle, where empirical risks associated with different bandwidths are compared.
Anisotropic oracle inequalities in noisy quantization
with density $f$ and $\epsilon_i$ are i. i. d.
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