statistics – Page 5 – Andrew Fairless, Ph.D.

What I Read: Russian Roulette

By Andrew Fairless on January 3, 2023November 5, 2022

The Russian Roulette: An Unbiased Estimator of the LimitBy Fabian Pedregosa.Sat 15 October 2022 “The Russian Roulette offers a simple way to construct an unbiased estimator for the limit ofContinue readingWhat I Read: Russian Roulette

What I Read: Bayesian Structural Timeseries

By Andrew Fairless on December 14, 2022November 5, 2022

Bayesian Structural Timeseries – ForecastingNathaniel FordeAug 15, 2022 “Bayesian structural timeseries assumes that the past is a guide to the future, and that if we can characterise the processes whichContinue readingWhat I Read: Bayesian Structural Timeseries

What I Read: Sins, Numerical Linear Algebra

By Andrew Fairless on December 7, 2022October 20, 2022

https://nhigham.com/2022/10/11/seven-sins-of-numerical-linear-algebra/ Seven Sins of Numerical Linear AlgebraNick HighamPosted on October 11, 2022 by Nick Higham “In numerical linear algebra we are concerned with solving linear algebra problems accurately and efficientlyContinue readingWhat I Read: Sins, Numerical Linear Algebra

What I Read: explainability, survival analysis

By Andrew Fairless on November 21, 2022September 27, 2022

https://medium.com/responsibleml/survex-model-agnostic-explainability-for-survival-analysis-94444e6ce83d survex: model-agnostic explainability for survival analysisMikołaj SpytekSep 19 “… survival models… tells us what is the probability of an event not happening until a given time t…. The complexity…Continue readingWhat I Read: explainability, survival analysis

What I Read: Neural Tangent Kernel

By Andrew Fairless on November 2, 2022September 27, 2022

https://lilianweng.github.io/posts/2022-09-08-ntk/ Some Math behind Neural Tangent KernelLilian WengSeptember 8, 2022 “Neural tangent kernel… leads to great insights into why neural networks with enough width can consistently converge to a globalContinue readingWhat I Read: Neural Tangent Kernel

What I Read: Causal Inference

By Andrew Fairless on October 25, 2022September 9, 2022

https://thegradient.pub/causal-inference-connecting-data-and-reality/ Causal Inference: Connecting Data and RealityWenwen Ding04.Sep.2022 “Causal inference is a theory that describes, discriminates, and measures causal relationships, developed from statistics.”

What I Read: Comparing quantiles at scale

By Andrew Fairless on October 3, 2022August 22, 2022

https://engineering.atspotify.com/2022/03/comparing-quantiles-at-scale-in-online-a-b-testing/ Comparing quantiles at scale in online A/B-testingMarch 23, 2022Published by Mårten Schultzberg (Senior Data Scientist) and Sebastian Ankargren (Data Scientist) “…we have been able to reduce the computational complexityContinue readingWhat I Read: Comparing quantiles at scale

What I Read: Concept Drift Without Labeled Data

By Andrew Fairless on September 26, 2022August 22, 2022

https://concept-drift.fastforwardlabs.com/ Inferring Concept Drift Without Labeled DataFF22Aug 2021 “…we explore broadly applicable approaches for dealing with concept drift when labeled data is not readily accessible. We’ll start by defining whatContinue readingWhat I Read: Concept Drift Without Labeled Data

What I Read: introduction to NumPyro

By Andrew Fairless on September 19, 2022August 22, 2022

https://dfm.io/posts/intro-to-numpyro/ An astronomer’s introduction to NumPyroDan Foreman-MackeyJul 28 2022 “In this post… I’ll focus primarily on providing an introduction to NumPyro, which is a probabilistic programming library that provides anContinue readingWhat I Read: introduction to NumPyro

What I Read: Supercharging A/B Testing

By Andrew Fairless on September 15, 2022August 3, 2022

Supercharging A/B Testing at Uber Supercharging A/B Testing at UberSergey Gitlin, Krishna Puttaswamy, Luke Duncan, Deepak Bobbarjung, and Arun Babu A S PJuly 21, 2022 “…building a correct and reliableContinue readingWhat I Read: Supercharging A/B Testing

Tag: statistics