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 windowsontheory.org
A blitz through classical statistical learning theory - Windows On Theory
| | hackmd.io
DeepNN Notes on Why Deep Networks Generalize - HackMD
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| | cgad.ski
When Gradient Descent Is a Kernel Method
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| | randorithms.com
Why is it Okay to Average Embeddings? - Randorithms
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| | People often summarize a "bag of items" by adding together the embeddings for each individual item. For example, graph neural networks summarize a section of...
| | alexanderetz.com
Understanding Bayes: A Look at the Likelihood | The Etz-Files
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| [This post has been updated and turned into a paper to be published in AMPPS] Much of the discussion in psychology surrounding Bayesian inference focuses on priors. Should we embrace priors, or should we be skeptical? When are Bayesian methods sensitive to specification of the prior, and when do the data effectively overwhelm it? Should...