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 rdrr.io
lm: Fitting Linear Models
| | pavpanchekha.com
Models from Models
2.7 parsecs away

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| | francisbach.com
Scaling laws of optimization - Machine Learning Research Blog
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| | [AI summary] This text discusses the scaling laws of optimization in machine learning, focusing on asymptotic expansions for both strongly convex and non-strongly convex cases. It covers the derivation of performance bounds using techniques like Laplace's method and the behavior of random minimizers. The text also explains the 'weird' behavior observed in certain plots, where non-strongly convex bounds become tight under specific conditions. The analysis connects theoretical results to practical considerations in optimization algorithms.
| | www.seascapemodels.org
seascapemodels
2.1 parsecs away

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| | [AI summary] A tutorial explaining the basics of General Linear Models using statistical concepts like linear equations, R programming simulations, and assumption checking for biological sciences.
| | golb.hplar.ch
Building a simple neural network with Java and JavaScript
9.1 parsecs away

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| [AI summary] The blog post details the author's experience implementing a feedforward neural network for digit recognition using Java and JavaScript, explaining the underlying algorithms, shared external libraries, and architectural decisions while reviewing an introductory book on the topic.