Feb 6, 2023 · Our framework allows the use of standard stochastic optimization algorithms to construct surrogates which can be minimized by any deterministic ...
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Though the surrogate is con- structed by using a stochastic gradient in the target space, it is a deterministic function with respect to the parame- ters and ...
Though the surrogate is constructed by using a stochastic gradient in the target space, it is a deterministic function with respect to the parameters and can be ...
Jul 23, 2023 · Our framework allows the use of standard stochastic optimization algorithms to construct surrogates which can be minimized by any deterministic ...
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Target Based Surrogates For Stochastic Optimization. The following is codebase allows for the reproduction of results following the paper "Target Based ...
Target-based Surrogates for Stochastic Optimization Poster
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Jul 21, 2023 · I'll be at ICML next week. I'll be: - Presenting our work on Target-based Surrogates for Stochastic Optimization (https://lnkd.in/e-6_nWc5) ...
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✓ Black-box structure for stochastic optimization: Can use any stochastic optimization algorithm to form surrogates which can then be optimized using any ...
2015. Target-based surrogates for stochastic optimization. JW Lavington, S ... MASAGA: A linearly-convergent stochastic first-order method for optimization on ...
This study presents a surrogate-assisted stochastic optimization inversion (SASOI) algorithm, a novel technique for static and dynamic parameter identification.