Three-Toed Sloth

Books to Read While the Algae Grow in Your Fur, June 2015

Attention conservation notice: I have no taste.

Walter Jon Williams, Brig of War

Mind candy historical adventure fiction: a tale of derring-do and angst in the nascent American navy during the war of 1812. It was written before Williams turned to science fiction, but in retrospect the seeds of a lot of his later concerns can be discerned here. In particular, the way the viewpoint protagonist is at once deeply embedded in an institution, indeed commits his life to it, and also an emotionally detached observer of that institution, will recur in many later books — I think Favian would have interesting conversations with Dagmar, Aiah or Martinez.

— No purchase link, since this is long out of print, but readily available from all the electronic book sellers.

(This is the only historical novel I know of which is set during the Napoleonic Wars, written by an American, and yet does not side with the British Empire. This partiality towards, if not wholehearted embrace of, the very system of global conquest, plunder and tyranny against which we fought the Revolution — the one which burnt Washington! — is astonishing. While I am reluctant to question the patriotism of our historical novelists, is any other conclusion available to the candid mind?)

Hilary Mantel, Wolf Hall

Mind candy: literary, historical competence porn*. Praise on my part is superfluous. Thanks to CM and TC for persuading me to start reading it, and for providing the term "competence porn". — Sequel.

*: "His speech is low and rapid, his manner assured; he is at home in courtroom or waterfront, bishop's palace or inn yard. He can draft a contract, train a falcon, draw a map, stop a street fight, furnish a house and fix a jury. He will quote you a nice point in the old authors, from Plato to Plautus and back again. He knows new poetry, and can say it in Italian. He works all hours, first up and last to bed. He makes money and he spends it. He will take a bet on anything."

Lászlo Györfi, Michael Kohler, Adam Krzyzak and Harro Walk, A Distribution-Free Theory of Nonparametric Regression

I can't remember having read a better, more comprehensive, clearer, volume on the theory of nonparametric regression. It is magnificently unconcerned with the practicalities of applied statistics, but rather relentlessly focused on determining what we can learn about conditional expectation functions, and how fast, when we assume basically nothing about those functions, other than that they are well-defined and we get IID data. (In the last chapters, it even allows for dependent data.) The coverage is largely organized around different sorts of models (kernel smoothing, histograms, regression trees, local polynomials, splines, orthogonal series expansions...), typically beginning by defining the model, considering the model class's expressive or approximative powers, and then looking at how quickly it will converge on the true regression function under various smoothness assumptions on the latter. Classical minimax theory is used to establish that smoother functions (e.g., those with many continuous derivative of low magnitude) can be learned more quickly than rougher functions, but naively, we'd seem to need to know how smooth the true function is in order to achieve these fast rates. Particularly nice models are "adaptive", they will automatically adjust to the data and learn almost as quickly as if they knew in advance how smooth the target was. Accordingly, a lot of space is given to looking at which methods are adaptive; many otherwise nice models don't adapt very well. Chapters on topics like minimax theory and empirical process theory break up the development of the models, introducing mathematical tools and general ideas as needed. Two chapters on cross-validation and data-splitting are particularly nice: everyone uses them, because they work, but there is surprisingly little theory about such important tools, and the results here are really quite illuminating.

In principle, all this book requires is a good grasp of probability theory and the math that goes along with it. Some of the proofs involve lengthy calculations, but none are tricky or mathematically deep, because they don't need to be. More realistically, I'd suggest some prior experience both with actually running non-parametric regressions (at the level of, say, Elements of Statistical Learning Theory), and with the characteristic concerns of non-parametric theory (say, All of Nonparametric Statistics, or Tsybakov). All of the major classes of regression models in common use around 2000 are included — and that includes all the models in common use today, except Gaussian processes. Serious statistical theorists interested in regression have already read the book; I recommend it for those into methodology or even applications, because it's very well done and it gives them a sense of what lies in the background.

(Thanks to Ryan T. for persuading me to not just browse this, as I'd been doing for a decade, but actually read it systematically.)

Stephen King, Finders Keepers

Mind candy: sequel to Mr. Mercedes, but enjoyable independently. This is because while some characters from that book are the nominal heroes here, the really central characters are new — an old thief and murderer, and an idealistic teenage boy, both, in different ways, the biggest fans of an (imaginary) mid-century American novelist who seems to interpolate between John Updike, J. D. Salinger and Henry Roth; the story is really about their rivalry for the manuscripts of his unpublished Great American Novels.

Patrick O'Brian, The Hundred Days

Ken Liu, The Grace of Kings

Mind candy: fantasy novel, based on the rise of the Han dynasty, with added squabbling gods, "silk-punk" technology, and glancing blows at patriarchy. I picked it up because of the quality of Liu's translation of The Three-Body Problem; I'd read the nigh-inevitable sequel.

John Sutton, Sunk Costs and Market Structure: Price Competition, Advertising, and the Evolution of Concentration

In this book, Sutton is looking at what determines the level of concentration in industries with fixed (set-up) costs, hence increasing returns and imperfect competition, and where advertising works, in the sense that by spending money on ads, firms can increase their sales at a given price. This tends to lead to concentrated markets, where a small number of firms capture a large proportion of sales. So far, so standard industrial organization. What sets Sutton's approach apart, and makes it really distinctive, is that Sutton realizes the equilibria of reasonable models of entry, pricing and advertising decisions are incredibly sensitive to model details, but there are inequalities which hold across very wide range of models. (He went on to elaborate on this in Technology and Market Structure, and give a programmatic statement in Marshall's Tendencies.) Specifically, for any given size of the market, he can put a lower bound on the degree of concentration (at equilibrium). The fixed costs of entry mean that this lower bound initially decreases with the size of the market. (The market has to be at least so big to pay back the cost of establishing multiple rival plants.) But if advertising is effective, after a certain point the lower bound actually increases in market size — it becomes advantageous for firms to ramp up the sunk costs of entering the market through intensive advertising.

While Sutton goes through some (comparatively) conventional econometric exercises to do things like estimate the lower bound on concentration as a function of the size of the market, the bulk of this book is taken up by wonderfully detailed qualitative applications of his theory to the evolution of concentration and corporate strategy in a wide range of food industries across the six largest industrial economies. This is somewhat dated, having been written in the 1980s, but still fascinating, for an admittedly-nerdy value of fascination. Even if you don't think you care about the comparative industrial organization of breakfast-cereal manufacturing, it's still a virtuoso performance in melding social-scientific theory with concrete history.

Charles Stross, Saturn's Children

Mind candy: it's hard out there for a fembot, especially when she was designed to be an "escort" for human males and humanity, and every other eukaryote, has been extinct for centuries. There are a lot of science-fictional in-jokes (e.g., the Scalzi museum of paleontology on Mars), and some of the revelations were things I got long before the protagonist did. (But maybe the reader was supposed to?) Overall, though, it works much better as a story in its own right than anything deliberately riffing off the later works of Robert Heinlein has any right to do.

Books to Read While the Algae Grow in Your Fur; Tales of Our Ancestors; Scientifiction and Fantastica; Pleasures of Detection, Portraits of Crime; The Dismal Science; Enigmas of Chance