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• W2138826651 startingPage "1255" @default.
• W2138826651 abstract "Consider multi-dimensional root finding when the equations are available only implicitly via a Monte Carlo simulation oracle that for any solution returns a vector of point estimates. We develop DARTS, a stochastic-approximation algorithm that makes quasi-Newton moves to a new solution whenever the current sample size is large compared to the estimated quality of the current solution and estimated sampling error. We show that DARTS converges in a certain precise sense, and discuss reasons to expect substantial computational efficiencies over traditional stochastic approximation variations." @default.
• W2138826651 created "2016-06-24" @default.
• W2138826651 creator A5047249580 @default.
• W2138826651 creator A5055129023 @default.
• W2138826651 date "2010-12-05" @default.
• W2138826651 modified "2023-09-26" @default.
• W2138826651 title "Root finding via darts: dynamic adaptive random target shooting" @default.
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• W2138826651 doi "https://doi.org/10.5555/2433508.2433661" @default.
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