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We prove novel algorithmic guarantees for several online problems in the smoothed analysis model. In this model, at each time an adversary chooses an input distribution with density function bounded above by 1σ times that of the uniform distribution; nature then samples an input from this distribution. Crucially, our results hold for adaptive adversaries that can choose an input distribution based on the decisions of the algorithm and the realizations of the inputs in the previous time steps.arXiv:2102.08446v2 fatcat:eq3326qer5aohmxnqmirqc3wcq