Markov – Andrew Fairless, Ph.D.

What I Read: Mamba Explained

By Andrew Fairless on June 10, 2024April 15, 2024

https://thegradient.pub/mamba-explained Mamba ExplainedKola Ayonrinde27.Mar.2024 “Mamba promises similar performance (and crucially similar scaling laws) as the Transformer whilst being feasible at long sequence lengths (say 1 million tokens).”

What I Read: data, product teams

By Andrew Fairless on April 20, 2023March 30, 2023

https://blog.duolingo.com/growth-model-duolingo/ Meaningful metrics: How data sharpened the focus of product teamsby Erin GustafsonFebruary 17, 2023 “Our Data Science team developed a growth framework that helped to grow DAUs by 4xContinue readingWhat I Read: data, product teams

What I Read: Causal Confounds, Sequential Decision

By Andrew Fairless on February 6, 2023December 4, 2022

https://blog.ml.cmu.edu/2022/11/28/causal-confounds-in-sequential-decision-making/ Causal Confounds in Sequential Decision MakingGokul SwamyNovember 28, 2022 “Using techniques from causal inference, we derive provably correct and scalable algorithms for sequential decision making in these sorts ofContinue readingWhat I Read: Causal Confounds, Sequential Decision

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