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stat.ML2025
Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs
Matthieu Cordonnier, Nicolas Keriven, Nicolas Tremblay +1
We study the convergence of message passing graph neural networks on random graph models to their continuous counterpart as the number of nodes tends to infinity. Until now, this c…
stat.ML2024
A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization
Mathieu Dagréou, Thomas Moreau, Samuel Vaiter +1
Bilevel optimization problems, which are problems where two optimization problems are nested, have more and more applications in machine learning. In many practical cases, the uppe…
stat.ML2024
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms
Mathieu Dagréou, Pierre Ablin, Samuel Vaiter +1
Bilevel optimization, the problem of minimizing a value function which involves the arg-minimum of another function, appears in many areas of machine learning. In a large scale emp…