After two long and rewarding days, CODE 2022 is a wrap. Here’s a biased look at some of my personal highlights; Keep in mind that this is far from a complete list: the conference was filled with quality content and due to the parallel nature of the talks, I missed more than half of them to begin with. Note: the plenary talks should be posted on... Read more 25 Oct 2022 - 9 minute read
Sometimes, statistical guarantees are not what they seem. Here, we discuss the implications of a classic work that demonstrates a paradox with the Bayesian approach to experiment analysis: when not careful, the experimenter runs the risk of running a frequentist analysis without realizing it. This can have important implications: when combined w... Read more 10 Sep 2022 - 7 minute read
Jax is a relatively new Python library aimed as a drop in replacement for Numpy for machine learning research. It sets itself apart due to its functional approach, which I find really enjoyable. Recently I have been playing around with implementing a simple RNN using Flax to get beyond the basics of Jax, but without adding all the bells and whis... Read more 20 Jun 2021 - 12 minute read
Based on work at Stitch Fix around experimentation with resource constraints and our introduction of the “virtual warehouse”, Greg Novak, Dave Spiegel and I wrote a post on the Multithreaded blog. We introduce the post with the following thought experiment: Suppose a group of squirrels is considering two possible strategies to survive a har... Read more 19 Nov 2020 - 2 minute read
Ramesh Johari, Virag Shah, and myself wrote an academic paper on “large scale experimentation” that introduces a framework on how to think about optimal testing when there are a lot of possible experiments to run. To accompany the more technical academic paper, I wrote a blog post with a more intuitive exposition of the main ideas for the Multi... Read more 08 Jul 2020 - less than 1 minute read