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Finite

Neural Information Processing Systems

We show that, surprisingly, the notion of optimal finite-time regret is not auniquely defined property in this context and that, in general, it is decoupled from theasymptotic rate.


Finite

Neural Information Processing Systems

We show that, surprisingly, the notion of optimal finite-time regret is not auniquely defined property in this context and that, in general, it is decoupled from theasymptotic rate.


Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality

Neural Information Processing Systems

We show that, surprisingly, the notion of optimal finite-time regret is not a uniquely defined property in this context and that, in general, it is decoupled from the asymptotic rate. We discuss alternative choices and propose a notion of finite-time optimality that we argue is meaningful .