6 citations · 13 across the 10 of their papers we have counts for
11 papers
Metrics and methods for a systematic comparison of fairness-aware machine learning algorithms
Gareth P. Jones, James M. Hickey, Pietro G. Di Stefano +3
Understanding and removing bias from the decisions made by machine learning models is essential to avoid discrimination against unprivileged groups. Despite recent progress in algo…
A k-core Decomposition Framework for Graph Clustering
Christos Giatsidis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis +4
Graph clustering or community detection constitutes an important task for investigating the internal structure of graphs, with a plethora of applications in several domains. Tradit…
AUC Optimisation and Collaborative Filtering
Charanpal Dhanjal, Romaric Gaudel, Stephan Clemencon
In recommendation systems, one is interested in the ranking of the predicted items as opposed to other losses such as the mean squared error. Although a variety of ways to evaluate…
On Recent Advances in Supervised Ranking for Metabolite Profiling
Charanpal Dhanjal, Stéphan Clémençon
This paper focuses on data arising from the field of metabolomics, a rapidly developing area concerned by the analysis of the chemical fingerprints (i.e. the metabolite profile). T…
Online Matrix Completion Through Nuclear Norm Regularisation
Charanpal Dhanjal, Romaric Gaudel, Stéphan Clémençon
It is the main goal of this paper to propose a novel method to perform matrix completion on-line. Motivated by a wide variety of applications, ranging from the design of recommende…
An SIR Graph Growth Model for the Epidemics of Communicable Diseases
Charanpal Dhanjal, Stéphan Clémençon
It is the main purpose of this paper to introduce a graph-valued stochastic process in order to model the spread of a communicable infectious disease. The major novelty of the SIR…