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blog.autarkaw.com | ||
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nhigham.com
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| | | | | Backward error is a measure of error associated with an approximate solution to a problem. Whereas the forward error is the distance between the approximate and true solutions, the backward error is how much the data must be perturbed to produce the approximate solution. For a function $latex f$ from $latex \mathbb{R}^n$ to $latex \mathbb{R}^n$ | |
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ataspinar.com
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| | | | | [latexpage] In this blog-post we will have a look at how Differential Equations (DE) can be solved numerically via the Finite Differences method. By solving differential equations we can run simula... | |
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www.johndcook.com
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| | | | | Notes on math and software: probability, approximations, special functions, regular expressions, Python, C++, R, etc. | |
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francisbach.com
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| | | [AI summary] The blog post discusses the spectral properties of kernel matrices, focusing on the analysis of eigenvalues and their estimation using tools like the matrix Bernstein inequality. It also covers the estimation of the number of integer vectors with a given L1 norm and the relationship between these counts and combinatorial structures. The post includes a detailed derivation of bounds for the difference between true and estimated eigenvalues, highlighting the role of the degrees of freedom and the impact of regularization in kernel methods. Additionally, it touches on the importance of spectral analysis in machine learning and its applications in various domains. | ||
