Blog, KDD and Optimization - Data Leaders Brief

Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

This is essentially the same as finding a truly useful objective to optimize. Recently, we presented some basic insights from our effort to measure and predict long-term effects at KDD 2015 [1]. In this blog post, we summarize that paper and refer you to it for details.

Modeling

Modeling Experimentation Knowledge Discovery KDD

Using Empirical Bayes to approximate posteriors for large "black box" estimators

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

Limitations Second order calibration, like ordinary calibration, is intended to be easy and useful, not comprehensive or optimal, and it shares some of ordinary calibration’s limitations. Both methods can be wrong for slices of the data while being correct on average, since they only use the covariate information through $t$.

KDD

KDD Testing Machine Learning Measurement

Data Leaders Brief

Experiment design and modeling for long-term studies in ads

Using Empirical Bayes to approximate posteriors for large "black box" estimators

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