Adaptive Learning of Polynomial Networks - Genetic...

Main
Computers - Computer Science
Adaptive Learning of Polynomial...

Adaptive Learning of Polynomial Networks - Genetic Programming, Backpropagation and Bayesian Methods

Nikolay Nikolaev

0 / 0

كم أعجبك هذا الكتاب؟

ما هي جودة الملف الذي تم تنزيله؟

قم بتنزيل الكتاب لتقييم الجودة

ما هي جودة الملفات التي تم تنزيلها؟

الفئات:

Computers - Computer Science

عام:

2006

الناشر:

Springer

اللغة:

english

الصفحات:

328

ISBN 10:

0306467623

ISBN 13:

9780306467622

ملف:

PDF, 15.49 MB

IPFS:

,

english, 2006

إقرأ علي الإنترنت

جاري التحويل إلى

التحويل إلى باء بالفشل

قد تكون في قائمة إهتماماتك

Nikolay Y. Nikolaev, Hitoshi Iba — Adaptive Learning of Polynomial Networks. Genetic Programming, Backpropagation and Bayesian Methods

Mukesh Patel, Vasant Honavar, Karthik Balakrishnan — Advances in the Evolutionary Synthesis of Intelligent Agents

Hugh Cartwright — Using Artificial Intelligence in Chemistry and Biology: A Practical Guide (Chapman & Hall Crc Research No)

MIT Press — Neural Computation, Volume 03 (1991) issue 1, 2, 3, 4

Gurney, Kevin — An Introduction to Neural Networks

Ali Kaveh — Applications of Artificial Neural Networks and Machine Learning in Civil Engineering

Raúl Rojas — Neural Networks: A Systematic Introduction

Michael Nielsen — Neural Networks and Deep Learning

Fyfe C. — Artificial neural networks

Moubachir Madani Fadoul — Python Machine Learning: Machine Learning And Deep Learning From Scratch Illustrated With Python, Scikit-Learn, Keras, Theano And Tensorflow

Hasanraza Ansari — Artificial Neural Network [Learn About Electronics]

Bishop — Neural Networks for Pattern Recognition

Gurney, K — Introduction to Neural Networks

Keith L. Downing — Intelligence Emerging: Adaptivity and Search in Evolving Neural Systems

Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka — Elements of artificial neural networks

Mukesh Patel, Vasant Honavar, Karthik Balakrishnan — Advances in the evolutionary synthesis of intelligent agents

John D. Kelleher — Deep Learning

John Kelleher — Deep Learning

JOHN D. KELLEHER — Deep Learning

Nikolaev N., Iba H. — Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods

Nikolay Nikolaev, Hitoshi Iba — Adaptive Learning of Polynomial Networks

Dirk Christian Mattfeld (auth.) — The Management of Transshipment Terminals: Decision Support for Terminal Operations in Finished Vehicle Supply Chains

Andries P. Engelbrecht — Computational Intelligence An Introduction

Masters, Timothy — Advanced algorithms for neural networks: a C++ sourcebook

Maureen Caudill — International Joint Conference on Neural Networks, January 15–19, 1990: Volume 1: Theory Track, Neural and Cognitive Sciences Track

Hugh Cartwright — Using Artificial Intelligence in Chemistry and Biology: A Practical Guide

Rudolf Kruse, Christian Borgelt, Christian Braune, Sanaz Mostaghim;Matthias Steinbrecher — Computational intelligence: a methodological introduction

Jeff Heaton — Introduction to the Math of Neural Networks

David S. Touretzky, Jeffrey L. Elman, Terrence J. Sejnowski — Connectionist Models. Proceedings of the 1990 Summer School

Dr. N D Lewis — Build Your Own Neural Network Today!: With step by step instructions showing you how to build them faster than you imagined possible using R

Niladri Syam, Rajeeve Kaul — Machine Learning and Artificial Intelligence in Marketing and Sales: Essential Reference for Practitioners and Data Scientists

Niladri Syam, Rajeeve Kaul — Machine Learning and Artificial Intelligence in Marketing and Sales: Essential Reference for Practitioners and Data Scientists

Kevin Gurney — An introduction to neural networks

Charu C. Aggarwal — Neural Networks and Deep Learning: A Textbook, 2nd Edition

Charu C. Aggarwal — Neural Networks and Deep Learning: A Textbook, 2nd Edition

أكثر المصطلحات والعبارات المستخدمة