SW-DRSO optimizes a tractable surrogate of worst-case expected loss over plausible inference-time corruptions using a barycentric adversary approximated via simplex weights.
Dyg-mamba: Continuous state space model- ing on dynamic graphs.Advances in Neural Information Processing Systems, 38:129101–129130, 2026a
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Distributionally Robust Set Representation Learning Under Inference-Time Element Corruption
SW-DRSO optimizes a tractable surrogate of worst-case expected loss over plausible inference-time corruptions using a barycentric adversary approximated via simplex weights.