Colt Proceedings 1990 PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Colt Proceedings 1990 PDF full book. Access full book title Colt Proceedings 1990.
Author | : COLT |
Publisher | : Elsevier |
Total Pages | : 405 |
Release | : 2012-12-02 |
Genre | : Computers |
ISBN | : 0323137709 |
Download COLT Proceedings 1990 Book in PDF, ePub and Kindle
COLT '90 covers the proceedings of the Third Annual Workshop on Computational Learning Theory, sponsored by the ACM SIGACT/SIGART, University of Rochester, Rochester, New York on August 6-8, 1990. The book focuses on the processes, methodologies, principles, and approaches involved in computational learning theory. The selection first elaborates on inductive inference of minimal programs, learning switch configurations, computational complexity of approximating distributions by probabilistic automata, and a learning criterion for stochastic rules. The text then takes a look at inductive identification of pattern languages with restricted substitutions, learning ring-sum-expansions, sample complexity of PAC-learning using random and chosen examples, and some problems of learning with an Oracle. The book examines a mechanical method of successful scientific inquiry, boosting a weak learning algorithm by majority, and learning by distances. Discussions focus on the relation to PAC learnability, majority-vote game, boosting a weak learner by majority vote, and a paradigm of scientific inquiry. The selection is a dependable source of data for researchers interested in the computational learning theory.
Author | : ACM Special Interest Group for Automata and Computability Theory |
Publisher | : Morgan Kaufmann |
Total Pages | : 408 |
Release | : 1990 |
Genre | : Artificial intelligence |
ISBN | : |
Download Proceedings of the Third Annual Workshop on Computational Learning Theory Book in PDF, ePub and Kindle
COLT '90 covers the proceedings of the Third Annual Workshop on Computational Learning Theory, sponsored by the ACM SIGACT/SIGART, University of Rochester, Rochester, New York on August 6-8, 1990. The book focuses on the processes, methodologies, principles, and approaches involved in computational learning theory. The selection first elaborates on inductive inference of minimal programs, learning switch configurations, computational complexity of approximating distributions by probabilistic automata, and a learning criterion for stochastic rules. The text then takes a look at inductive identification of pattern languages with restricted substitutions, learning ring-sum-expansions, sample complexity of PAC-learning using random and chosen examples, and some problems of learning with an Oracle. The book examines a mechanical method of successful scientific inquiry, boosting a weak learning algorithm by majority, and learning by distances. Discussions focus on the relation to PAC learnability, majority-vote game, boosting a weak learner by majority vote, and a paradigm of scientific inquiry. The selection is a dependable source of data for researchers interested in the computational learning theory.
Author | : David. H Wolpert |
Publisher | : CRC Press |
Total Pages | : 311 |
Release | : 2018-03-05 |
Genre | : Mathematics |
ISBN | : 0429972156 |
Download The Mathematics Of Generalization Book in PDF, ePub and Kindle
This book provides different mathematical frameworks for addressing supervised learning. It is based on a workshop held under the auspices of the Center for Nonlinear Studies at Los Alamos and the Santa Fe Institute in the summer of 1992.
Author | : |
Publisher | : |
Total Pages | : 0 |
Release | : 1990 |
Genre | : |
ISBN | : |
Download Conference proceedings Book in PDF, ePub and Kindle
Author | : Gerhard Lakemeyer |
Publisher | : Springer Science & Business Media |
Total Pages | : 372 |
Release | : 1994-06-28 |
Genre | : Computers |
ISBN | : 9783540581079 |
Download Foundations of Knowledge Representation and Reasoning Book in PDF, ePub and Kindle
The papers collected in this book cover a wide range of topics in asymptotic statistics. In particular up-to-date-information is presented in detection of systematic changes, in series of observation, in robust regression analysis, in numerical empirical processes and in related areas of actuarial sciences and mathematical programming. The emphasis is on theoretical contributions with impact on statistical methods employed in the analysis of experiments and observations by biometricians, econometricians and engineers.
Author | : APEC. 5, 1990, Los Angeles, Calif.. |
Publisher | : |
Total Pages | : 839 |
Release | : 1990 |
Genre | : |
ISBN | : |
Download Conference Proceedings 1990 Book in PDF, ePub and Kindle
Author | : Leo Breiman |
Publisher | : SIAM |
Total Pages | : 740 |
Release | : 1968-01-01 |
Genre | : Mathematics |
ISBN | : 9780898712964 |
Download Probability Book in PDF, ePub and Kindle
Approximation of Large-Scale Dynamical Systems
Author | : United States. Department of Justice |
Publisher | : |
Total Pages | : 286 |
Release | : |
Genre | : Emigration and immigration law |
ISBN | : |
Download 8 USC 1324 ... Proceeding Book in PDF, ePub and Kindle
Author | : Canadian Society for Computational Studies of Intelligence. Conference |
Publisher | : Toronto, Ont. : The Society |
Total Pages | : 278 |
Release | : 1992 |
Genre | : Artificial intelligence |
ISBN | : |
Download Proceedings of the Ninth Biennial Conference of the Canadian Society for Computational Studies of Intelligence Book in PDF, ePub and Kindle
Author | : Óscar Martinez Mozos |
Publisher | : Springer Science & Business Media |
Total Pages | : 145 |
Release | : 2010-02-04 |
Genre | : Technology & Engineering |
ISBN | : 3642112099 |
Download Semantic Labeling of Places with Mobile Robots Book in PDF, ePub and Kindle
During the last years there has been an increasing interest in the area of service robots. Under this category we find robots working in tasks such as elderly care, guiding, office and domestic assistance, inspection, and many more. Service robots usually work in indoor environments designed for humans, with offices and houses being some of the most typical examples. These environments are typically divided into places with different functionalities like corridors, rooms or doorways. The ability to learn such semantic categories from sensor data enables a mobile robot to extend its representation of the environment, and to improve its capabilities. As an example, natural language terms like corridor or room can be used to indicate the position of the robot in a more intuitive way when communicating with humans. This book presents several approaches to enable a mobile robot to categorize places in indoor environments. The categories are indicated by terms which represent the different regions in these environments. The objective of this work is to enable mobile robots to perceive the spatial divisions in indoor environments in a similar way as people do. This is an interesting step forward to the problem of moving the perception of robots closer to the perception of humans. Many approaches introduced in this book come from the area of pattern recognition and classification. The applied methods have been adapted to solve the specific problem of place recognition. In this regard, this work is a useful reference to students and researchers who want to introduce classification techniques to help solve similar problems in mobile robotics.