Jul 8, 2021 · We propose and analyze a randomized zeroth-order approach based on approximating the exact gradient byfinite differences computed in a set of orthogonal random ...
Aug 2, 2022 · We propose and analyze a randomized zeroth-order optimization method based on approximating the exact gradient by finite differences ...
Aug 2, 2022 · We propose and analyze a randomized zeroth-order optimization method based on approximating the exact gradient by finite differences computed ...
We propose and analyze a randomized zeroth-order optimization method based on approximating the exact gradient by finite differences computed in a set of ...
Nov 15, 2021 · We propose and analyze a randomized zeroth-order approach based on approximating the exact gradient by finite differences computed in a set of ...
Sep 9, 2024 · We propose and analyze a randomized zeroth-order optimization method based on approximating the exact gradient by finite differences computed in ...
Zeroth-order optimization with orthogonal random directions. https://doi.org/10.1007/s10107-022-01866-9 ·. Journal: Mathematical Programming, 2022, № 1-2, ...
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What is zeroth order optimization?
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Our method exploits a smooth approximation of the target function and we prove that it approximates its gradient on a subset of random orthogonal directions. We ...
Nov 22, 2023 · This paper proposed to improve Zero-Order optimization in deep nerual network learning. It first points out that Coordinate-wise Gradient Estimation (CGE) is ...
In zeroth-order optimization, the algorithms only access the objective function value to find a designed solution. We review three main lines of research to ...