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grigory.github.io
| | djalil.chafai.net
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| | This post is devoted to few convex and compact sets of matrices that I like. The set \( {\mathcal{C}_n} \) of correlation matrices. A real \( {n\times n} \) matrix \( {C} \) is a correlation matrix when \( {C} \) is symmetric, semidefinite positive, with unit diagonal. This means that \[ C_{ii}=1, \quad C_{ji}=C_{ji},\quad \left\geq0 \] for every \(...
| | analytixon.com
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| | Deep Reinforcement Learning based Recommendation (DRR) Recommendation is crucial in both academia and industry, and various techniques are proposed such as content-based collaborative filtering, ma...
| | www.randomservices.org
4.7 parsecs away

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| | [AI summary] The text covers various topics in probability and statistics, including continuous distributions, empirical density functions, and data analysis. It discusses the uniform distribution, rejection sampling, and the construction of continuous distributions without probability density functions. The text also includes data analysis exercises involving empirical density functions for body weight, body length, and gender-specific body weight.
| | mathematicaloddsandends.wordpress.com
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| The function $latex f(x) = x \log x$ occurs in various places across math/statistics/machine learning (e.g. in the definition of entropy), and I thought I'd put a list of properties of the function here that I've found useful. Here is a plot of the function: $latex f$ is defined on $latex (0, \infty)$. The only...