Matches in Harvard for { <http://id.lib.harvard.edu/aleph/008775849/catalog> ?p ?o. }
Showing items 1 to 25 of
25
with 100 items per page.
- catalog abstract "A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data. Highly applicable to a variety of computer science and robotics fields, this book offers lucid coverage of the theory as a whole. Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.".
- catalog contributor b12301024.
- catalog created "c1998.".
- catalog date "1998".
- catalog date "c1998.".
- catalog dateCopyrighted "c1998.".
- catalog description "A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data. Highly applicable to a variety of computer science and robotics fields, this book offers lucid coverage of the theory as a whole. Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.".
- catalog description "Includes bibliographical references (p. 723-732) and index.".
- catalog description "Introduction: The Problem of Induction and Statistical Inference -- I. Theory of Learning and Generalization. 1. Two Approaches to the Learning Problem. App. to Ch. 1. Methods for Solving III-Posed Problems. 2. Estimation of the Probability Measure and Problem of Learning. 3. Conditions for Consistency of Empirical Risk Minimization Principle. 4. Bounds on the Risk for Indicator Loss Functions. App. to Ch. 4. Lower Bounds on the Risk of the ERM Principle. 5. Bounds on the Risk for Real-Valued Loss Functions. 6. The Structural Risk Minimization Principle. App. to Ch. 6. Estimating Functions on the Basis of Indirect Measurements. 7. Stochastic III-Posed Problems. 8. Estimating the Values of Function at Given Points.".
- catalog extent "xxiv, 736 p. :".
- catalog hasFormat "Statistical learning theory.".
- catalog identifier "0471030031 (acid-free paper)".
- catalog isFormatOf "Statistical learning theory.".
- catalog isPartOf "Adaptive and learning systems for signal processing, communications, and control".
- catalog issued "1998".
- catalog issued "c1998.".
- catalog language "eng".
- catalog publisher "New York : Wiley,".
- catalog relation "Statistical learning theory.".
- catalog subject "006.3/1 21".
- catalog subject "Computational learning theory.".
- catalog subject "Q325.7 .V38 1998".
- catalog tableOfContents "Introduction: The Problem of Induction and Statistical Inference -- I. Theory of Learning and Generalization. 1. Two Approaches to the Learning Problem. App. to Ch. 1. Methods for Solving III-Posed Problems. 2. Estimation of the Probability Measure and Problem of Learning. 3. Conditions for Consistency of Empirical Risk Minimization Principle. 4. Bounds on the Risk for Indicator Loss Functions. App. to Ch. 4. Lower Bounds on the Risk of the ERM Principle. 5. Bounds on the Risk for Real-Valued Loss Functions. 6. The Structural Risk Minimization Principle. App. to Ch. 6. Estimating Functions on the Basis of Indirect Measurements. 7. Stochastic III-Posed Problems. 8. Estimating the Values of Function at Given Points.".
- catalog title "Statistical learning theory / Vladimir N. Vapnik.".
- catalog type "text".