Books to Read While the Algae Grow in Your Fur, May 2021
Attention conservation notice: I have no taste.
- Lauren Henderson, Dead White Female and Too Many Blondes
- Mind candy mystery from the 1990s. I read all of the later books in
this series with great delight as they came out, and while these first two are a bit rougher than
her later work, they're still quite tasty, especially if you remember the
fashions and mores of the time.
- (I've included links to the old paper editions, but you'd be better off tracking down the electronic re-issues.)
- Andre Norton, Gates to the Witch World (= Witch World, Web of the Witch World, Year of the Unicorn)
- I don't remember what led me to pick this up, but damn could
Norton write, and write compressedly. (For instance, a lot of the
plot of the first two books here got recycled for the plot of Martha Wells's
[very good] Fall of Ile-Rein
series.) I had in fact read Year of the Unicorn as a boy,
but remembered only a few fragments of the story.
- ObLinkage: James Davis Nicoll on Witch World, Web of the Witch World, and Year of the Unicorn
- Taylor Adams, No Exit
- Mind-candy thriller, which I think conforms to every one of the classical dramatic unities.
- L. G. Estrella, Two Necromancers, a Bureaucrat, and an Army of Golems and Two Necromancer, a Dragon, and a Vampire
- Mind candy of the fluffiest sort. These have the pleasure, and the feel,
of a Dungeons & Dragons campaign where vastly over-powered PCs engage in
cheerfully cartoonish banter, violence and pillage. It's a bit of a guilty,
regressive pleasure for me, but a real pleasure nonetheless. (No links because
they're only available in electronic formats.)
On a different note, over the semester I re-read a lot of textbooks and
monographs for the
undergrad statistical learning class, so I provide some
links here for the ones I mined for examples and problem sets
found especially useful:
- Anthony and Bartlett, Neural Network Learning: Theoretical Foundations
- Boucheron, Lugosi and Massart, Concentration Inequalities: A Nonasymptotic Theory of Independence
- Cesa-Bianchi and Lugosi, Prediction, Learning, and Games
- Györfi, Kohler, Krzyzak and Walk, A Distribution-Free Theory of Nonparametric Regression
- Kearns and Vazirani, An Introduction to Computational Learning Theory
- Massart, Concentration Inequalities and Model Selection
- Mohri, Rostamizadeh and Talwalkar, Foundations of Machine Learning
- Pollard, Convergence of Stochastic Processes
- Shawe-Taylor and Cristianini, Kernel Methods for Pattern Analysis
- Vapnik, The Nature of Statistical Learning Theory
Books to Read While the Algae Grow in Your Fur;
Scientifiction and Fantastica;
Pleasures of Detection, Portraits of Crime;
Enigmas of Chance;
Posted at May 31, 2021 23:59 | permanent link