{"product_id":"information-theory-meets-power-laws","title":"Information Theory Meets Power Laws","description":"\u003cp\u003e\u003cb\u003eDiscover new theoretical connections between stochastic phenomena and the structure of natural language with this powerful volume!\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eInformation Theory Meets Power Laws: Stochastic Processes and Language Models\u003c\/i\u003e presents readers with a novel subtype of a probabilistic approach to language, which is based on statistical laws of texts and their analysis by means of information theory. The distinguished author insightfully and rigorously examines the linguistic and mathematical subject matter while eschewing needlessly abstract and superfluous constructions.\u003c\/p\u003e \u003cp\u003eThe book begins with a less formal treatment of its subjects in the first chapter, introducing its concepts to readers without mathematical training and allowing those unfamiliar with linguistics to learn the book’s motivations. Despite its inherent complexity, \u003ci\u003eInformation Theory Meets Power Laws: Stochastic Processes and Language Models \u003c\/i\u003eis a surprisingly approachable treatment of idealized mathematical models of human language.\u003c\/p\u003e \u003cp\u003eThe author succeeds in developing some of the theory underlying fundamental stochastic and semantic phenomena, like strong nonergodicity, in a way that has not previously been seriously attempted. In doing so, he covers topics including:\u003c\/p\u003e \u003cul\u003e\n\u003cli\u003eZipf’s and Herdan’s laws for natural language\u003c\/li\u003e\n\u003cli\u003ePower laws for information, repetitions, and correlations\u003c\/li\u003e\n\u003cli\u003eMarkov, finite-state,and Santa Fe processes\u003c\/li\u003e\n\u003cli\u003eBayesian and frequentist  interpretations of probability\u003c\/li\u003e\n\u003cli\u003eErgodic decomposition, Kolmogorov complexity, and universal coding\u003c\/li\u003e\n\u003cli\u003eTheorems about facts and words\u003c\/li\u003e\n\u003cli\u003eInformation measures for fields\u003c\/li\u003e\n\u003cli\u003eRényi entropies, recurrence times, and subword complexity\u003c\/li\u003e\n\u003cli\u003eAsymptotically mean stationary processes\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eWritten primarily for mathematics graduate students and professionals interested in information theory or discrete stochastic processes, \u003ci\u003eInformation Theory Meets Power Laws: Stochastic Processes and Language Models \u003c\/i\u003ealso belongs on the bookshelves of doctoral students and researchers in artificial intelligence, computational and quantitative linguistics as well as physics of complex systems.\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Product","offer_id":54219731206488,"sku":"9781119625278","price":106.99,"currency_code":"EUR","in_stock":true}],"url":"https:\/\/agendabookshop.com\/products\/information-theory-meets-power-laws","provider":"Agenda Bookshop","version":"1.0","type":"link"}