13 citations · 20 across the 3 of their papers we have counts for
5 papers
All of the Fairness for Edge Prediction with Optimal Transport
Charlotte Laclau, Ievgen Redko, Manvi Choudhary +1
Machine learning and data mining algorithms have been increasingly used recently to support decision-making systems in many areas of high societal importance such as healthcare, ed…
Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond
Nina Vesseron, Ievgen Redko, Charlotte Laclau
The theoretical analysis of deep neural networks (DNN) is arguably among the most challenging research directions in machine learning (ML) right now, as it requires from scientists…
Rank-one partitioning: formalization, illustrative examples, and a new cluster enhancing strategy
Charlotte Laclau, Franck Iutzeler, Ievgen Redko
In this paper, we introduce and formalize a rank-one partitioning learning paradigm that unifies partitioning methods that proceed by summarizing a data set using a single vector t…
Cross-lingual Document Retrieval using Regularized Wasserstein Distance
Georgios Balikas, Charlotte Laclau, Ievgen Redko +1
Many information retrieval algorithms rely on the notion of a good distance that allows to efficiently compare objects of different nature. Recently, a new promising metric called…
Co-clustering through Optimal Transport
Charlotte Laclau, Ievgen Redko, Basarab Matei +2
In this paper, we present a novel method for co-clustering, an unsupervised learning approach that aims at discovering homogeneous groups of data instances and features by grouping…