pml-book
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probml
"Probabilistic Machine Learning" - a book series by Kevin Murphy
I added back a commented out paragraph on Cramer-Rao lower bound to sec 4.7.6.2 (Variance of an estimator). Context: https://news.ycombinator.com/item?id=30552869
add footnote discucssing some issues with CIFAR-100 dataset (based on https://twitter.com/rasbt/status/1554458573396234241?s=27&t=eZTRpRz4X7g__rl3d7vNqA)
In some places $f$ is used to indicate the true function and in other places a variable in $p(f | \mathcal{D}_n)$. Some of the suggestions below are to try to...
[KR21a] M. Khan and H. Rue. "The Bayesian Learning Rule". In: (2022). arXiv: [2107.04562](https://arxiv.org/abs/2107.04562). page 265, line 30: in this section -> In this section page 266, line 28: $\exp(R(\boldsymbol{\theta}))$...
The link to Stephen Boyd's presentation needs the extension `.pdf` in the URL, lest it return a 404 error, i.e. http://ee263.stanford.edu/lectures/min-norm needs to be http://ee263.stanford.edu/lectures/min-norm.pdf instead.
Three m's instead of two in `symmetric` ``` In Section 7.4.3.1, we show that a symmmetric matrix is positive definite ... ```
> If $m < n$ (short, fat) and the rows of $\mathbf{A}$ are linearly independent (so $\mathbf{A}$ is full rank), then the pseudo inverse ... I believe should be: >...
The second minus should be a plus: $$+\sum_{x} p(x) \log p(x)$$
Book 1, formula 8.149: $\mathbf{Ł}(\boldsymbol{\theta}, q_n | \mathbf{y}_n)$ Book 1, formula 8.150: $\mathbf{Ł}(\boldsymbol{\theta}, q_n)$ Book 2, formulas 6.134 and 6.135: $\mathbf{Ł}(\boldsymbol{\theta}, q_n | \mathbf{y}_n)$ In my opinion, Book 2 is...
line 8: cals -> calls line 23: Student T -> Student line 29: discussed -> discuss