Jan 24, 2021 · We construct a family of functions suitable for establishing lower bounds on the oracle complexity of first-order minimization of smooth strongly-convex ...
On the oracle complexity of smooth strongly convex minimization
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In this paper, we study the performance of deterministic first-order methods for approximating the solution of unconstrained strongly-convex minimization ...
Sep 12, 2024 · We present a bundle method for solving convex semi-infinite minmax problems which allows inexact solution of the inner maximization. The method ...
Jun 14, 2021 · We present a shorter and easier to follow proof for establishing the exact minimax risk for non-strongly-convex smooth convex minimization ...
The method is optimal in the sense that its worst-case bound exactly matches the lower bound on the oracle complexity for the class of problems, ...
Oct 22, 2024 · We construct a family of functions suitable for establishing lower bounds on the oracle complexity of first-order minimization of smooth ...
The method is optimal in the sense that its worst-case bound exactly matches the lower bound on the oracle complexity for the class of problems, meaning that no ...
Near-optimal method for highly smooth convex optimization · Mathematics, Computer Science. Annual Conference Computational Learning Theory · 2019.
In this note, we consider the complexity of optimizing a highly smooth (Lipschitz $k$-th order derivative) and strongly convex function, via calls to a ...
Missing: minimization. | Show results with:minimization.
The problem of smooth and convex minimization plays a key role in a various range of applications, including signal and image processing, communications, ...