Dynamic Regret in Online Convex Optimization with Indicator Switching Costs
A meta-learning framework: a set of randomized lazy FTRL base learners restarted at dyadic time scales, aggregated by a movement-aware master that mixes their proposal densities and samples actions via maximal coupling of consecutive mixtures is proposed.
N. Mhaisen, George Iosifidis
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