Inductive Logic

Inductive Logic
Author: Dov M. Gabbay
Publisher: Elsevier
Total Pages: 801
Release: 2011-05-27
Genre: Mathematics
ISBN: 0080931693

Inductive Logic is number ten in the 11-volume Handbook of the History of Logic. While there are many examples were a science split from philosophy and became autonomous (such as physics with Newton and biology with Darwin), and while there are, perhaps, topics that are of exclusively philosophical interest, inductive logic — as this handbook attests — is a research field where philosophers and scientists fruitfully and constructively interact. This handbook covers the rich history of scientific turning points in Inductive Logic, including probability theory and decision theory. Written by leading researchers in the field, both this volume and the Handbook as a whole are definitive reference tools for senior undergraduates, graduate students and researchers in the history of logic, the history of philosophy, and any discipline, such as mathematics, computer science, cognitive psychology, and artificial intelligence, for whom the historical background of his or her work is a salient consideration. - Chapter on the Port Royal contributions to probability theory and decision theory - Serves as a singular contribution to the intellectual history of the 20th century - Contains the latest scholarly discoveries and interpretative insights

Pattern Recognition Applications and Methods

Pattern Recognition Applications and Methods
Author: Maria De Marsico
Publisher: Springer
Total Pages: 250
Release: 2018-06-15
Genre: Computers
ISBN: 3319936476

This book contains revised and extended versions of selected papers from the 6th International Conference on Pattern Recognition, ICPRAM 2017, held in Porto, Portugal, in February 2017. The 13 full papers presented were carefully reviewed and selected from 139 initial submissions. They aim at making visible and understandable the relevant trends of current research on pattern recognition.

Differential Geometry and Differential Equations

Differential Geometry and Differential Equations
Author: Chaohao Gu
Publisher: Springer
Total Pages: 259
Release: 2006-11-15
Genre: Mathematics
ISBN: 3540478833

The DD6 Symposium was, like its predecessors DD1 to DD5 both a research symposium and a summer seminar and concentrated on differential geometry. This volume contains a selection of the invited papers and some additional contributions. They cover recent advances and principal trends in current research in differential geometry.

Mathematical Analysis of Machine Learning Algorithms

Mathematical Analysis of Machine Learning Algorithms
Author: Tong Zhang
Publisher: Cambridge University Press
Total Pages: 470
Release: 2023-07-31
Genre: Computers
ISBN: 1009115553

The mathematical theory of machine learning not only explains the current algorithms but can also motivate principled approaches for the future. This self-contained textbook introduces students and researchers of AI to the main mathematical techniques used to analyze machine learning algorithms, with motivations and applications. Topics covered include the analysis of supervised learning algorithms in the iid setting, the analysis of neural networks (e.g. neural tangent kernel and mean-field analysis), and the analysis of machine learning algorithms in the sequential decision setting (e.g. online learning, bandit problems, and reinforcement learning). Students will learn the basic mathematical tools used in the theoretical analysis of these machine learning problems and how to apply them to the analysis of various concrete algorithms. This textbook is perfect for readers who have some background knowledge of basic machine learning methods, but want to gain sufficient technical knowledge to understand research papers in theoretical machine learning.

Invariant Markov Processes Under Lie Group Actions

Invariant Markov Processes Under Lie Group Actions
Author: Ming Liao
Publisher: Springer
Total Pages: 370
Release: 2018-06-28
Genre: Mathematics
ISBN: 3319923242

The purpose of this monograph is to provide a theory of Markov processes that are invariant under the actions of Lie groups, focusing on ways to represent such processes in the spirit of the classical Lévy-Khinchin representation. It interweaves probability theory, topology, and global analysis on manifolds to present the most recent results in a developing area of stochastic analysis. The author’s discussion is structured with three different levels of generality:— A Markov process in a Lie group G that is invariant under the left (or right) translations— A Markov process xt in a manifold X that is invariant under the transitive action of a Lie group G on X— A Markov process xt invariant under the non-transitive action of a Lie group GA large portion of the text is devoted to the representation of inhomogeneous Lévy processes in Lie groups and homogeneous spaces by a time dependent triple through a martingale property. Preliminary definitions and results in both stochastics and Lie groups are provided in a series of appendices, making the book accessible to those who may be non-specialists in either of these areas. Invariant Markov Processes Under Lie Group Actions will be of interest to researchers in stochastic analysis and probability theory, and will also appeal to experts in Lie groups, differential geometry, and related topics interested in applications of their own subjects.