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Apr 5, 2021 · We study the secure stochastic convex optimization problem. A learner aims to learn the optimal point of a convex function through sequentially querying a ( ...
In this work, we study the secure stochastic convex optimization problem, in which the learner aims to optimize the accuracy, i.e., obtain an accurate estimate ...
Summary and Contributions: This paper investigates the secure stochastic convex optimization problem. In this model, a learner seeks to minimize a convex ...
Apr 5, 2021 · We study the secure stochastic convex optimization problem. A learner aims to learn the optimal point of a convex function through ...
Dec 6, 2020 · We study the secure stochastic convex optimization problem. A learner aims to learn the optimal point of a convex function through ...
Apr 5, 2021 · A generic secure learning protocol is presented that achieves the matching upper bound up to logarithmic factors and a general template ...
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It is proved that if f grows at least as fast as x − xf,S around its minimum, for some κ > 1, then the optimal rate of learning f(xf,S) is Θ(T − κ 2κ−2 ).
Hence, the optimal query complexity is significantly lower under the minimax formulation than the Bayesian one, as our results will show next. The Bayesian ...
Convex optimization with feedback is a paradigm in which an learner repeatedly queries an external data source in order to identify the optimal solution of a ...