2015 Optimization Strategy Uncertainty 
The Unofficial Google Data Science Blog
APRIL 23, 2024
If the relationship of $X$ to $Y$ can be approximated as quadratic (or any polynomial), the objective and constraints as linear in $Y$, then there is a way to express the optimization as a quadratically constrained quadratic program (QCQP). Crucially, it takes into account the uncertainty inherent in our experiments.
Cloudera
SEPTEMBER 29, 2021
In a world rife with uncertainty, governments need to ensure that their citizens’ health and well-being are taken care of even as they seek to keep their economies afloat. The Singapore Health Services (SingHealth) has also used data to optimize operations during the pandemic.
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The Unofficial Google Data Science Blog
JULY 22, 2020
by ALEXANDER WAKIM Ramp-up and multi-armed bandits (MAB) are common strategies in online controlled experiments (OCE). These strategies involve changing assignment weights during an experiment. The first is a strategy called ramp-up and is advised by many experts in the field [1].
The Unofficial Google Data Science Blog
MARCH 31, 2016
In the context of prediction problems, another benefit is that the models produce an estimate of the uncertainty in their predictions: the predictive posterior distribution. arXiv preprint arXiv:1506.04416 (2015). [6] Applied Stochastic Models in Business and Industry, 31 (2015): 37-49. bandit problems). Bayesian dark knowledge."
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