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Test-Time Compensated Representation Learning for Extreme Traffic Forecasting
In this paper, we identify an underexplored problem in multivariate traffic series prediction: extreme events.
CorrAttack: Black-box Adversarial Attack with Structured Search
We show that searching over the structured space can be approximated by a time-varying contextual bandits problem, where the attacker takes feature of the associated arm to make modifications of the input, and receives an immediate reward as the reduction of the loss function.
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