19 citations · 64 across the 31 of their papers we have counts for
5 papers · 1 filter
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…
Improving Few-Shot Learning through Multi-task Representation Learning Theory
Quentin Bouniot, Ievgen Redko, Romaric Audigier +2
In this paper, we consider the framework of multi-task representation (MTR) learning where the goal is to use source tasks to learn a representation that reduces the sample complex…
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…
A survey on domain adaptation theory: learning bounds and theoretical guarantees
Ievgen Redko, Emilie Morvant, Amaury Habrard +2
All famous machine learning algorithms that comprise both supervised and semi-supervised learning work well only under a common assumption: the training and test data follow the sa…