OCO-S$^2$: Online Convex Optimization with Stateful Costs and
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OCO-S$^2$: Online Convex Optimization with Stateful Costs and Sparse Communication
Announce Type: replace Abstract: We study \textsc{OCO-S$^2$}, an online convex optimization setting in which decisions drive a stable dynamical state, losses are incurred along the induced state trajectory, and first-order feedback is available only through sparse block communication with partial participation. This coupling creates a dynamic-regret problem beyond pointwise OCO: the learner updates and holds decisions at the block scale, whereas the hindsight comparator may vary at the...