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| | djalil.chafai.net
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| | Convergence in law to a constant. Let \( {{(X_n)}_{n\geq1}} \) be a sequence of random variables defined on a common probability space \( {(\Omega,\mathcal{A},\mathbb{P})} \), and taking their values in a metric space \( {(E,d)} \) equipped with its Borel sigma-field. It is well known that if \( {{(X_n)}_{n\geq1}} \) converges in law as \( {n\rightarrow\infty} \) to some Dirac...
| | aakinshin.net
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| | In [[carling-outlier-detector]], I evaluated the probability of outlier detection for samples from the Normal distribution across different outlier detectors. I performed numerical simulations for small sample sizes, then confidently extrapolated the result...
| | danieltakeshi.github.io
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| | In my STAT 210A class, we frequently have to deal with the minimum of asequence of independent, identically distributed (IID) random variables. Thishappens b...
| | robotchinwag.com
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| Deriving the gradients for the backward pass for matrix multiplication using tensor calculus