Algebraic Geometry and Statistical Learning Theory
Sure to be influential, Watanabe's book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.
Dimensions of Register Variation: A Cross-Linguistic Comparison
The book extends and refines the research and methodology reported in the author’s ground-breaking Variation Across Speech and Writing, and adds for the first time a diachronic dimension. In it he gives a linguistic analysis of register in four widely differing languages: English, Nukulaelae Tuvaluan, Korean, and Somali. Striking similarities as well as differences emerge, allowing to predict for the first time cross-linguistic universals of register variation.
This book focuses on the linguistic representation of temporality in the verbal domain and its interaction with the syntax and semantics of verbs, arguments, and modifiers. Leading scholars explore the division of labour between syntax, compositional semantics, and lexical semantics in the encoding of event structure, encompassing event participants and the temporal properties associated with events.
English translation of standard mathematical work on theory of numbers, first published in Latin in 1801. "Among the greatest mathematical treatises of all fields and periods."--Asger Aaboe. Summary: Great Classic Math Book from a Master This is an incredible work, painstakingly and lovingly translated by someone with more patience than I might ever have. Thank God there are people out there who can do such tedious things so we can all enjoy these great works in English.
This undergraduate textbook is written for a junior/senior level course on linear optimization. Unlike other texts, the treatment follows the "modified Moore method" approach in which examples and proof opportunities are worked into the text in order to encourage students to develop some of the content through their own experiments and arguments while they are reading the text. Additionally, the focus is on the mathematics underlying the ideas of optimizing linear functions under linear constraints and the algorithms used to solve them.
