hierarchical – Andrew Fairless, Ph.D.

What I Read: Inducing hierarchy for multi-class classification

By Andrew Fairless on February 22, 2024January 7, 2024

https://arxiv.org/abs/2102.10263 Inducing a hierarchy for multi-class classification problemsHayden S. Helm, Weiwei Yang, Sujeeth Bharadwaj, Kate Lytvynets, Oriana Riva, Christopher White, Ali Geisa, Carey E. Priebe “In applications where categorical labelsContinue readingWhat I Read: Inducing hierarchy for multi-class classification

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: Aristotle, Deep Learning

By Andrew Fairless on March 17, 2022March 12, 2022

https://thegradient.pub/how-aristotle-is-fixing-deep-learnings-flaws/ How Aristotle is Fixing Deep Learning’s FlawsPaul J. Blazek17.Feb.2022 “…Aristotle’s logic still stands strong, poignantly describing the building blocks of human reasoning. Yet many of the key ingredients describedContinue readingWhat I Read: Aristotle, Deep Learning

What I Read: The Brain Processes Speech in Parallel With Other Sounds

By Andrew Fairless on November 9, 2021October 24, 2021

https://www.quantamagazine.org/the-brain-processes-speech-in-parallel-with-other-sounds-20211021/ The Brain Processes Speech in Parallel With Other SoundsJordana CepelewiczOctober 21, 2021“Scientists thought that the brain’s hearing centers might just process speech along with other sounds. But new workContinue readingWhat I Read: The Brain Processes Speech in Parallel With Other Sounds

What I Read: Bayesian Hierarchical Modelling at Scale

By Andrew Fairless on April 2, 2021March 21, 2021

https://florianwilhelm.info/2020/10/bayesian_hierarchical_modelling_at_scale/ Finally! Bayesian Hierarchical Modelling at ScaleFlorian WilhelmDate Oct. 01, 2020 “In this blog post, I want to draw your attention to the somewhat dusty Bayesian Hierarchical Modelling. Modern techniquesContinue readingWhat I Read: Bayesian Hierarchical Modelling at Scale

What I Read: Approximate Nearest Neighbor Search in Vespa

By Andrew Fairless on February 21, 2021January 26, 2021

https://blog.vespa.ai/approximate-nearest-neighbor-search-in-vespa-part-1/ Approximate Nearest Neighbor Search in Vespa – Part 1Geir StorliPrinciple Vespa Engineer “Searching for the nearest neighbors of a data point in a high dimensional vector space is anContinue readingWhat I Read: Approximate Nearest Neighbor Search in Vespa

What I Read: Neural Architecture Search

By Andrew Fairless on January 26, 2021December 31, 2020

https://lilianweng.github.io/lil-log/2020/08/06/neural-architecture-search.html Neural Architecture SearchAug 6, 2020 by Lilian Weng “Automatically learning and evolving network topologies is not a new idea (Stanley & Miikkulainen, 2002). In recent years, the pioneering workContinue readingWhat I Read: Neural Architecture Search

What I Read: HDBSCAN and Density-Based Clustering

By Andrew Fairless on December 10, 2020November 29, 2020

https://towardsdatascience.com/understanding-hdbscan-and-density-based-clustering-121dbee1320e?gi=26e320393f44 Understanding HDBSCAN and Density-Based ClusteringA comprehensive top-down introduction to the inner workings of the HDBSCAN clustering algorithm and key concepts of density-based clusteringPepe BerbaJan 17 “Therefore, a clustering algorithmContinue readingWhat I Read: HDBSCAN and Density-Based Clustering

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