4 papers
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…