4 citations · 4 across the 7 of their papers we have counts for
9 papers
A Comprehensive View of Fairness through Distributional Stability
Gayane Taturyan, Charlotte Laclau, Stephan Clémencon
We view fairness as a property of distributional stability. Rather than assessing a predictor under a fixed data distribution, we study how its predictions change under perturbatio…
Doing well with less! On Sampling Techniques for Empirical Pairwise Loss Estimation/Minimization
Louise Davy, Stephan Clémençon, Charlotte Laclau
Many machine learning problems, including similarity learning, ranking, and clustering, rely on empirical pairwise loss functions whose quadratic computational cost quickly becomes…
On Gossip Algorithms for Machine Learning with Pairwise Objectives
Igor Colin, Aurélien Bellet, Stephan Clémençon +1
In the IoT era, information is more and more frequently picked up by connected smart sensors with increasing, though limited, storage, communication and computation abilities. Whet…
Active Bipartite Ranking with Smooth Posterior Distributions
James Cheshire, Stephan Clémençon
In this article, bipartite ranking, a statistical learning problem involved in many applications and widely studied in the passive context, is approached in a much more general \te…
Beyond Kemeny Medians: Consensus Ranking Distributions Definition, Properties and Statistical Learning
Stephan Clémençon, Ekhine Irurozki
In this article we develop a new method for summarizing a ranking distribution, \textit{i.e.} a probability distribution on the symmetric group , beyond the classic…
Weak Signals and Heavy Tails: Learning Theory meets Extreme Value Analysis
Stephan Clémençon, Anne Sabourin
The masses of data now available have opened up the prospect of discovering weak signals using machine-learning algorithms, with a view to predictive or interpretation tasks. As th…
On Ranking-based Tests of Independence
Myrto Limnios, Stéphan Clémençon
In this paper we develop a novel nonparametric framework to test the independence of two random variables and with unknown respective marginals an…
A Bipartite Ranking Approach to the Two-Sample Problem
Stephan Clémençon, Myrto Limnios, Nicolas Vayatis
The two-sample problem, which consists in testing whether independent samples on are drawn from the same (unknown) distribution, finds applications in many areas. It…
Concentration Inequalities for Two-Sample Rank Processes with Application to Bipartite Ranking
Stéphan Clémençon, Myrto Limnios, Nicolas Vayatis
The ROC curve is the gold standard for measuring the performance of a test/scoring statistic regarding its capacity to discriminate between two statistical populations in a wide va…