2 links tagged with all of: optimization + experimentation
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Meta has launched Ax 1.0, an open-source platform that uses machine learning to streamline complex experimentation. It employs Bayesian optimization to help researchers efficiently identify optimal configurations across various applications, from AI model tuning to infrastructure optimization.
The article outlines six indicators that suggest an experiment should be repeated, such as solid impact results, almost significant p-values, and cases where initial results seem "too good to be true." It emphasizes the importance of revisiting past experiments for better insights and improving statistical power.