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On the Link Between Polynomials and Optimization, Part 1
| | francisbach.com
Sums-of-squares for dummies: a view from the Fourier domain - Machine Learning Research Blog
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| | blog.omega-prime.co.uk
L1 regression solved six ways
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| | The most fundamental technique in statistical learning is ordinary least squares (OLS) regression. If we have a vector of observations \(y\) and a matrix of features associated with each observation \(X\), then we assume the observations are a linear function of the features plus some (iid) random noise, \(\epsilon\):
| | jeremykun.wordpress.com
Duality for the SVM - Math Programming
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| | This post is a sequel toFormulating the Support Vector Machine Optimization Problem. The Karush-Kuhn-Tucker theorem Generic optimization problems are hard to solve efficiently. However, optimization problems whose objective and constraints have special structureoften succumb to analytic simplifications. For example, if you want to optimize a linear function subject to linear equality constraints, one can compute...
| | www.jeremymorgan.com
How to Get Started With PyTorch
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| Want to learn about PyTorch? Of course you do. This tutorial covers PyTorch basics, creating a simple neural network, and applying it to classify handwritten digits.