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stat.ML2025
Adaptive collaboration for online personalized distributed learning with heterogeneous clients
Constantin Philippenko, Batiste Le Bars, Kevin Scaman +1
We study the problem of online personalized decentralized learning with statistically heterogeneous clients collaborating to accelerate local training. An important challenge i…
stat.ML2025
Graph Alignment via Birkhoff Relaxation
Sushil Mahavir Varma, Irène Waldspurger, Laurent Massoulié
We consider the graph alignment problem, wherein the objective is to find a vertex correspondence between two graphs that maximizes the edge overlap. The graph alignment problem is…