14 citations · 26 across the 6 of their papers we have counts for
7 papers
Fighting Selection Bias in Statistical Learning: Application to Visual Recognition from Biased Image Databases
Stephan Clémençon, Pierre Laforgue, Robin Vogel
In practice, and especially when training deep neural networks, visual recognition rules are often learned based on various sources of information. On the other hand, the recent de…
A Multiclass Classification Approach to Label Ranking
Stephan Clémençon, Robin Vogel
In multiclass classification, the goal is to learn how to predict a random label , valued in with , based upon observing a r.v. ,…
Weighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling
Robin Vogel, Mastane Achab, Stéphan Clémençon +1
We consider statistical learning problems, when the distribution of the training observations differs from the distribution involved in the risk o…
Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints
Robin Vogel, Aurélien Bellet, Stephan Clémençon
Many applications of AI involve scoring individuals using a learned function of their attributes. These predictive risk scores are then used to take decisions based on whether the…
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…
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
Robin Vogel, Aurélien Bellet, Stéphan Clémençon
The performance of many machine learning techniques depends on the choice of an appropriate similarity or distance measure on the input space. Similarity learning (or metric learni…