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Experimental results show that the proposed hyperbolic manifold constrained tabular neural network is effective, and HTNN ranks first among 36 methods on 200 classification datasets and third among 34 methods on 100 regression datasets.
A personalized federated sparse adaptation framework with a heterogeneous temporal mixture-of-experts (MoE) adapter placed after the pretrained TSFM representation, showing that federated TSFM adaptation should be both client-aware and backbone-aware.
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