Randomization has proven extremely useful in helping to design simple, efficient geometric algorithms; see, e.g., [15, 22, 23, 25, 26, 27, 33, 34, 38, 63].
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Oct 16, 2020 · We present an approach for approximately solving discrete-time stochastic optimal-control problems by combining direct trajectory optimization, deterministic ...
Abstract—We present an approach for approximately solving discrete-time stochastic optimal-control problems by combining direct trajectory optimization ...
Abstract. Probabilistic sampling-based algorithms, such as the probabilistic roadmap (PRM) and the rapidly-exploring random tree.
Jun 23, 2005 · 'Deterministic sampling and optimization' published in 'System Modelling and Optimization'
We present a randomized optimization approach that drastically reduces the enormous computational cost of optimizing designs under many load cases.
problem. Given the pattern, a sample of its positions is carefully selected whose size is at most logarithmic. (the deterministic sample).
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Oct 26, 2020 · This project aims at developing optimal deterministic methods for statistical sampling / statistical observations, in contrast to commonly ...
Aug 6, 2024 · This blog post will delve into this topic by examining advanced data processing techniques like deterministic sampling to showcase how Instagram leverages ...