108 citations · 365 across the 55 of their papers we have counts for
7 papers · 1 filter
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure
Guillaume Staerman, Pavlo Mozharovskyi, Stephan Clémençon
With the ubiquity of sensors in the IoT era, statistical observations are becoming increasingly available in the form of massive (multivariate) time-series. Formulated as unsupervi…
A Multivariate Extreme Value Theory Approach to Anomaly Clustering and Visualization
Maël Chiapino, Stéphan Clémençon, Vincent Feuillard +1
In a wide variety of situations, anomalies in the behaviour of a complex system, whose health is monitored through the observation of a random vector X = (X1,. .. , X d) valued in…
On Tree-based Methods for Similarity Learning
Stéphan Clémençon, Robin Vogel
In many situations, the choice of an adequate similarity measure or metric on the feature space dramatically determines the performance of machine learning methods. Building automa…
Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning
Robin Vogel, Aurélien Bellet, Stephan Clémençon +2
The development of cluster computing frameworks has allowed practitioners to scale out various statistical estimation and machine learning algorithms with minimal programming effor…
Empirical Risk Minimization under Random Censorship: Theory and Practice
Guillaume Ausset, Stéphan Clémençon, François Portier
We consider the classic supervised learning problem, where a continuous non-negative random label (i.e. a random duration) is to be predicted based upon observing a random vect…
Statistical Learning from Biased Training Samples
Stephan Clémençon, Pierre Laforgue
With the deluge of digitized information in the Big Data era, massive datasets are becoming increasingly available for learning predictive models. However, in many practical situat…