3 papers
cs.LG2026
Parametrized Power-Iteration Clustering for Directed Graphs
Gwendal Debaussart-Joniec, Harry Sevi, Matthieu Jonckheere +1
Vertex-level clustering for directed graphs (digraphs) remains challenging as edge directionality breaks the key assumptions underlying popular spectral methods, which also incur t…
math.PR2025
On the instability of local learning algorithms: Q-learning can fail in infinite state spaces
Urtzi Ayesta, Sergey Foss, Matthieu Jonckheere +1
We investigate the challenges of applying model-free reinforcement learning algorithms, like online Q-learning, to infinite state space Markov Decision Processes (MDPs). We first i…
stat.ML2025
Generalized Dirichlet Energy and Graph Laplacians for Clustering Directed and Undirected Graphs
Harry Sevi, Gwendal Debaussart-Joniec, Malik Hacini +2
Clustering in directed graphs remains a fundamental challenge due to the asymmetry in edge connectivity, which limits the applicability of classical spectral methods originally des…