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Fast rates for noisy clustering
The effect of errors in variables in empirical minimization is investigated. Given a loss $l$ and a set of decision rules $\mathcal{G}$, we prove a general upper bound... -
Anisotropic oracle inequalities in noisy quantization
The effect of errors in variables in quantization is investigated. We prove general exact and non-exact oracle inequalities with fast rates for an empirical... -
Adaptive Noisy Clustering
The problem of adaptive noisy clustering is investigated. Given a set of noisy observations $Z_i=X_i+\epsilon_i$, $i=1, \ldots, n$, the goal is to design clusters... -
Noisy classification with boundary assumptions
We address the problem of classification when data are collected from two samples with measurement errors. This problem turns to be an inverse problem and requires a...
