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 francisbach.com
Scaling laws of optimization - Machine Learning Research Blog
| | fa.bianp.net
On the Convergence of the Unadjusted Langevin Algorithm
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| | The Langevin algorithm is a simple and powerful method to sample from a probability distribution. It's a key ingredient of some machine learning methods such as diffusion models and differentially private learning. In this post, I'll derive a simple convergence analysis of this method in the special case when the ...
| | dustintran.com
On asymptotic convergence of averaged SGD | Dustin Tran
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| | Stochastic gradient descent (SGD) has seen wide application for learning problems on large scale data, whether this be for generalized linear models [6], SVM...
| | michael-lewis.com
A machine learning glossary for hackers ยท Michael I Lewis
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| | This is a short summary of some of the terminology used in machine learning, with an emphasis on neural networks. I've put it together primarily to help my own understanding, phrasing it largely in non-mathematical terms. As such it may be of use to others who come from more of a programming than a mathematical background.
| | zserge.com
AI or ain't: Neural Networks
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| Neural network and deep learning introduction for those who skipped the math class but wants to follow the trend