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;