A Computational Approach to Statistical Learning
- ISBN-10
- 0367570610
- ISBN-13
- 9780367570613
- Category
- Estimation theory
- Pages
- 362
- Language
- English
- Published
- 2020-06-30
- Publisher
- CRC Press
- Authors
- Michael Kane, Taylor Arnold, Bryan W. Lewis
Description
This book synthesizes those techniques from numerical analysis, algorithms, data structures, and optimization theory mostcommonly employed in statistics and machine learning. We provide concrete applications of these methods by giving complete reference implementations for a large set of the most commonly used statistical estimators. The goal is
Get the book
Other editions
Similar books
-
On the Probability of Correct Selection when K is Large
By Jason WilsonGiven k populations, it is often desirable to select the best t. The body of ranking and selection literature from 1954 to 1992 thoroughly addressed this problem for small k...
-
Robust Estimates of Location: Survey and Advances
By David F. Andrews, Peter J. Bickel, Frank R. HampelThis book was written as the result of a study undertaken to establish the interaction of these three components over as large a range as possible. Originally published in 1972.
-
Indefinite-Quadratic Estimation and Control: A Unified Approach to H2 and H-infinity Theories
By Babak Hassibi, Ali H. Sayed, Thomas KailathH °° optimality criteria for LMS and backpropagation. In Advances in Neural Information Processing Systems, volume 6, J .D. Cowan, G. Tesauro, and J. Alspector, editors, pages 351-359, Morgan-Kaufmann, New York, ...
-
Tong ji xin hao chu li ji chu: Gu ji yu jian ce li lun. Estimation Theory. Detection Theory
本书是一部经典的有关统计信号处理的权威著作.全书分为两卷, 分别讲解了统计信号处理基础的估计理论和检测理论.卷I详细介绍了经典估计理论和贝叶斯估计, 总结了各种估计方法, ...
-
Empirical Process Techniques for Dependent Data
By Michael Sørensen, Thomas Mikosch, Herold DehlingEmpirical Process Techniques for Dependent Data
-
Optimality: The Second Erich L. Lehmann Symposium
By Javier RojoVou Vol Vo B ( t ) ( 1.5 ) 0 V012 ( a ) V021 W Vo2 V022 = i 11/2 1/2 ( c ) V1 1/2 + Wy Vø1 Vø2 = B ( 1 ) – B ( 1/2 ) = Vø / 2 – Wo - - V V ( b ) FIG 2. ( a ) Binary tree for interpolation of Brownian motion , B ( t ) .
-
Fundamentals of Statistical Signal Processing: Estimation Theory
By Steven M. Kay"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for ...
-
Fundamentals Of Statistical Processing, Volume 2: Detection Theory
By Steven M. Kay"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for ...
-
Introduction To Statistical Signal Processing With Applications,1/e
By Mandyam Dhati SrinathIntroduction To Statistical Signal Processing With Applications,1/e