108 citations · 365 across the 55 of their papers we have counts for
5 papers · 2 filters
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…
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…
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…
Functional Isolation Forest
Guillaume Staerman, Pavlo Mozharovskyi, Stephan Clémençon +1
For the purpose of monitoring the behavior of complex infrastructures (e.g. aircrafts, transport or energy networks), high-rate sensors are deployed to capture multivariate data, g…