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عنوان
Maximum Entropy and Bayesian Methods

پدید آورنده
edited by Gary J. Erickson, Joshua T. Rychert, C. Ray Smith.

موضوع
Artificial intelligence.,Coding theory.,Computational complexity.,Distribution (Probability theory).,Mathematics.,Statistics.

رده

کتابخانه
Center and Library of Islamic Studies in European Languages

محل استقرار
استان: Qom ـ شهر: Qom

Center and Library of Islamic Studies in European Languages

تماس با کتابخانه : 32910706-025

INTERNATIONAL STANDARD BOOK NUMBER

(Number (ISBN
9789401061117
(Number (ISBN
9789401150286

NATIONAL BIBLIOGRAPHY NUMBER

Number
b408880

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
Maximum Entropy and Bayesian Methods
General Material Designation
[Book]
Other Title Information
Boise, Idaho, USA, 1997 Proceedings of the 17th International Workshop on Maximum Entropy and Bayesian Methods of Statistical Analysis /
First Statement of Responsibility
edited by Gary J. Erickson, Joshua T. Rychert, C. Ray Smith.

.PUBLICATION, DISTRIBUTION, ETC

Place of Publication, Distribution, etc.
Dordrecht :
Name of Publisher, Distributor, etc.
Imprint: Springer,
Date of Publication, Distribution, etc.
1998.

SERIES

Series Title
Fundamental Theories of Physics, An International Book Series on The Fundamental Theories of Physics: Their Clarification, Development and Application ;
Volume Designation
98

CONTENTS NOTE

Text of Note
Massive Inference and Maximum Entropy -- CV-NP Bayesianism by MCMC -- Which Algorithms are Feasible? A Maxent Approach -- Maximum Entropy, Likelihood and Uncertainty: A Comparison -- Probabilistic Methods for Data Fusion -- Whence the Laws of Probability? -- Bayesian Group Analysis -- Symmetry-Group Justification of Maximum Entropy Method and Generalized Maximum Entropy Methods in Image Processing -- Probability Synthesis, How to Express Probabilities in Terms of Each Other -- Inversion Based on Computational Simulations -- Model Comparison with Energy Confinement Data from Large Fusion Experiments -- Deconvolution Based on Experimentally Determined Apparatus Functions -- A Bayesian Approach for the Determination of the Charge Density from Elastic Electron Scattering Data -- Integrated Deformable Boundary Finding Using Bayesian Strategies -- Shape Reconstruction in X-Ray Tomography from a Small Number of Projections Using Deformable Models -- An Empirical Model of Brain Shape -- Difficulties Applying Blind Source Separation Techniques to EEG and MEG -- The History of Probability Theory -- We Must Choose the Simplest Physical Theory: Levin-Li-Vitányi Theorem and Its Potential Physical Applications -- Maximum Entropy and Acausal Processes: Astrophysical Applications and Challenges -- Computational Exploration of the Entropic Prior Over Spaces of Low Dimensionality -- Environmentally-Oriented Processing of Multi-Spectral Satellite Images: New Challenges for Bayesian Methods -- Maximum Entropy Approach to Optimal Sensor Placement for Aerospace Non-Destructive Testing -- Maximum Entropy Under Uncertainty.
0

SUMMARY OR ABSTRACT

Text of Note
This volume has its origin in the Seventeenth International Workshop on Maximum Entropy and Bayesian Methods, MAXENT 97. The workshop was held at Boise State University in Boise, Idaho, on August 4 -8, 1997. As in the past, the purpose of the workshop was to bring together researchers in different fields to present papers on applications of Bayesian methods (these include maximum entropy) in science, engineering, medicine, economics, and many other disciplines. Thanks to significant theoretical advances and the personal computer, much progress has been made since our first Workshop in 1981. As indicated by several papers in these proceedings, the subject has matured to a stage in which computational algorithms are the objects of interest, the thrust being on feasibility, efficiency and innovation. Though applications are proliferating at a staggering rate, some in areas that hardly existed a decade ago, it is pleasing that due attention is still being paid to foundations of the subject. The following list of descriptors, applicable to papers in this volume, gives a sense of its contents: deconvolution, inverse problems, instrument (point-spread) function, model comparison, multi sensor data fusion, image processing, tomography, reconstruction, deformable models, pattern recognition, classification and group analysis, segmentation/edge detection, brain shape, marginalization, algorithms, complexity, Ockham's razor as an inference tool, foundations of probability theory, symmetry, history of probability theory and computability. MAXENT 97 and these proceedings could not have been brought to final form without the support and help of a number of people.

OTHER EDITION IN ANOTHER MEDIUM

International Standard Book Number
9789401061117

PIECE

Title
Springer eBooks

PARALLEL TITLE PROPER

Parallel Title
Proceedings of the 17th International Workshop on Maximum Entropy and Bayesian Methods of Statistical Analysis

TOPICAL NAME USED AS SUBJECT

Artificial intelligence.
Coding theory.
Computational complexity.
Distribution (Probability theory).
Mathematics.
Statistics.

PERSONAL NAME - PRIMARY RESPONSIBILITY

Erickson, Gary J.

PERSONAL NAME - ALTERNATIVE RESPONSIBILITY

Rychert, Joshua T.
Smith, C. Ray.

CORPORATE BODY NAME - ALTERNATIVE RESPONSIBILITY

SpringerLink (Online service)

ORIGINATING SOURCE

Date of Transaction
20190307155400.0

ELECTRONIC LOCATION AND ACCESS

Electronic name
 مطالعه متن کتاب 

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