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). However, joint optimization is possible by increasing both $x_1$ and $x_2$ at the same time.
The Unofficial Google Data Science Blog
OCTOBER 7, 2015
This is essentially the same as finding a truly useful objective to optimize. accounting for effects "orthogonal" to the randomization used in experimentation. Recently, we presented some basic insights from our effort to measure and predict long-term effects at KDD 2015 [1].
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The Unofficial Google Data Science Blog
JULY 22, 2020
Instead, we focus on the case where an experimenter has decided to run a full traffic ramp-up experiment and wants to use the data from all of the epochs in the analysis. When there are changing assignment weights and time-based confounders, this complication must be considered either in the analysis or the experimental design.
The Unofficial Google Data Science Blog
JUNE 30, 2016
In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. It should be noted that inverse probability weighting is not generally optimal (i.e., This is often referred to as the positivity assumption. the curse of dimensionality).
Occam's Razor
JANUARY 9, 2012
All while constantly optimizing your portfolio via controlled experiments. I told 20 people that Nikon's site is slow and profoundly sub-optimal on mobile. Companies get entrenched in what they know and end up constantly optimizing for what's always worked, meanwhile the world changes and these companies die, albeit slowly.
Domino Data Lab
JULY 2, 2019
SQL optimization provides helpful analogies, given how SQL queries get translated into query graphs internally , then the real smarts of a SQL engine work over that graph. The query graph provides metadata that gets leveraged for optimizations at multiple layers of the relational database stack. A Sampler of Program Synthesis.
Domino Data Lab
FEBRUARY 4, 2019
Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. Ensure a culture that supports a steady process of learning and experimentation. Friction ensued. You’ll need to read the papers.
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