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Neural solvers can now effectively handle the complexities of multi-agent coordination and multi-objective trade-offs in routing problems, outperforming traditional heuristics.
Personalized federated learning gets a boost from Fed-GAME, which uses a graph attention mixture-of-experts to dynamically aggregate client updates, outperforming SOTA methods on time-series forecasting tasks.
