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All About Sample-Size Calculations for A/B Testing: Novel Extensions and Practical Guide



While there exists a large amount of literature on the general challenges and best practices for trustworthy online A/B testing, there are limited studies on sample size estimation, which plays a crucial role in trustworthy and efficient A/B testing that ensures the resulting inference has a sufficient power and type I error control. For example, when the sample size is under-estimated the statistical inference, even with the correct analysis methods, will not be able to detect the true significant improvement leading to misinformed and costly decisions. This paper addresses this fundamental…



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Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials

In practice, training using federated learning can be orders of magnitude slower than standard centralized training. This severely limits the amount of experimentation and tuning that can be done, making it challenging to obtain good performance on a...

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024 Article Source link and Credit

Introducing Apple’s On-Device and Server Foundation Models

Introducing Apple’s On-Device and Server Foundation Models Article Source link and Credit