Author: Publisher:
ISBN:
Category : Canada
Languages : en
Pages : 1316
Book Description
Canadiana
Author: Mon Nouveau Programme d'Introduction a la Science de l'Informatique
Author: St-Amand, LéoPublisher: Montréal : Guérin
ISBN: 9782760122659
Category : Computer terminals
Languages : fr
Pages : 186
Book Description
Mon nouveau programme d'introduction à la science de l'informatique
Author: Léo St-AmandPublisher: Montréal : Guérin
ISBN: 9782760114098
Category : Algorithms
Languages : fr
Pages : 186
Book Description
Bibliotheca Medica Canadiana
Author: Français Interactif
Author: Karen KeltonPublisher:
ISBN: 9781937963200
Category :
Languages : en
Pages :
Book Description
This textbook includes all 13 chapters of Français interactif. It accompanies www.laits.utexas.edu/fi, the web-based French program developed and in use at the University of Texas since 2004, and its companion site, Tex's French Grammar (2000) www.laits.utexas.edu/tex/ Français interactif is an open acess site, a free and open multimedia resources, which requires neither password nor fees. Français interactif has been funded and created by Liberal Arts Instructional Technology Services at the University of Texas, and is currently supported by COERLL, the Center for Open Educational Resources and Language Learning UT-Austin, and the U.S. Department of Education Fund for the Improvement of Post-Secondary Education (FIPSE Grant P116B070251) as an example of the open access initiative.
The Postmodern Condition
Author: Jean-François LyotardPublisher: U of Minnesota Press
ISBN: 9780816611737
Category : Philosophy
Languages : en
Pages : 142
Book Description
In this book it explores science and technology, makes connections between these epistemic, cultural, and political trends, and develops profound insights into the nature of our postmodernity.
Guide to Foreign and International Legal Citations
Author: Publisher:
ISBN:
Category : Annotations and citations (Law)
Languages : en
Pages : 300
Book Description
"Formerly known as the International Citation Manual"--p. xv.
Canadian Journal of Earth Sciences
Author: Predicting Structured Data
Author: Neural Information Processing Systems FoundationPublisher: MIT Press
ISBN: 0262026171
Category : Algorithms
Languages : en
Pages : 361
Book Description
State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.
An Introduction to Computational Learning Theory
Author: Michael J. KearnsPublisher: MIT Press
ISBN: 9780262111935
Category : Computers
Languages : en
Pages : 230
Book Description
Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.