embedding – Page 4 – Andrew Fairless, Ph.D.

What I Read: Why I’m lukewarm on graph neural networks

By Andrew Fairless on March 10, 2021March 7, 2021

https://www.singlelunch.com/2020/12/28/why-im-lukewarm-on-graph-neural-networks/ Why I’m lukewarm on graph neural networksMatt RangerFebruary 16, 2020 “I’m only lukewarm on Graph Neural Networks (GNNs)…. I think some progress can come of this research, but we’reContinue readingWhat I Read: Why I’m lukewarm on graph neural networks

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: Building a Gigascale ML Feature Store

By Andrew Fairless on February 18, 2021January 18, 2021

https://doordash.engineering/2020/11/19/building-a-gigascale-ml-feature-store-with-redis/ Building a Gigascale ML Feature Store with Redis, Binary Serialization, String Hashing, and CompressionNovember 19, 2020 21 Minute Read Data, Machine Learning 36Arbaz Khan Zohaib Sibte Hassan “When aContinue readingWhat I Read: Building a Gigascale ML Feature Store

What I Read: HuggingFace Transformers

By Andrew Fairless on February 18, 2021January 18, 2021

https://medium.com/georgian-impact-blog/how-to-incorporate-tabular-data-with-huggingface-transformers-b70ac45fcfb4 How to Incorporate Tabular Data with HuggingFace TransformersGeorgianOct 23 “At Georgian, we find ourselves working with supporting tabular feature information as well as unstructured text data. We found thatContinue readingWhat I Read: HuggingFace Transformers

What I Read: Transformer Architecture

By Andrew Fairless on January 21, 2021December 29, 2020

https://blog.exxactcorp.com/a-deep-dive-into-the-transformer-architecture-the-development-of-transformer-models/ Deep LearningA Deep Dive Into the Transformer Architecture – The Development of Transformer ModelsMarketing, July 14, 2020 0 11 min readTransformers for Natural Language Processing “There’s no better timeContinue readingWhat I Read: Transformer Architecture

What I Read: ScaNN, Efficient Vector Similarity Search

By Andrew Fairless on January 14, 2021December 23, 2020

https://www.googblogs.com/announcing-scann-efficient-vector-similarity-search/ Announcing ScaNN: Efficient Vector Similarity SearchPosted by Philip Sun, Software Engineer, Google Research “Based on this intuition, we more heavily penalize quantization error that is parallel to the originalContinue readingWhat I Read: ScaNN, Efficient Vector Similarity Search

What I Read: scalable graph machine learning

By Andrew Fairless on December 3, 2020November 28, 2020

https://www.kdnuggets.com/2019/12/scalable-graph-machine-learning.html Scalable graph machine learning: a mountain we can climb?By Kevin Jung, Software Engineer at CSIRO Data61 “In this article, we will take a closer look at scalability for graphContinue readingWhat I Read: scalable graph machine learning

What I Read: Medical device surveillance with electronic health records

By Andrew Fairless on November 28, 2020November 28, 2020

https://www.nature.com/articles/s41746-019-0168-z Alison Callahan, Jason A. Fries, Christopher Ré, James I. Huddleston III, Nicholas J. Giori, Scott Delp & Nigam H. Shahnpj Digital Medicine volume 2, Article number: 94 (2019) “OurContinue readingWhat I Read: Medical device surveillance with electronic health records

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