Контакты/Проезд  Доставка и Оплата Помощь/Возврат
История
  +7(495) 980-12-10
  пн-пт: 10-18 сб,вс: 11-18
  shop@logobook.ru
Российская литература
   
    Поиск книг                    Поиск по списку ISBN Расширенный поиск    
Найти
  Зарубежные издательства Российские издательства  
Авторы | Каталог книг | Издательства | Новинки | Учебная литература | Акции | Хиты | |
 
Войти
Регистрация  Забыли?

Network Embedding: Theories, Methods, and Applications, Yang Cheng, Liu Zhiyuan, Tu Cunchao
Yang Cheng, Liu Zhiyuan, Tu Cunchao Network Embedding: Theories, Methods, and Applications 9781636390444

Варианты приобретения
Цена: 12751.00р.
Кол-во:
 о цене
Наличие: Отсутствует. Возможна поставка под заказ.

При оформлении заказа до: 2025-09-01
Ориентировочная дата поставки: начало Октября
При условии наличия книги у поставщика.
Добавить в корзину
в Мои желания

Автор: Yang Cheng, Liu Zhiyuan, Tu Cunchao
Название:  Network Embedding: Theories, Methods, and Applications
ISBN: 9781636390444
Издательство: Mare Nostrum (Eurospan)
Классификация:
Искусственный интеллект

Нейронные сети и нечеткие системы

ISBN-10: 1636390447
Обложка/Формат: Paperback
Страницы: 242
Вес: 0.43 кг.
Дата издания: 30.03.2021
Серия: Synthesis lectures on artificial intelligence and machine learning
Язык: English
Размер: 23.50 x 19.05 x 0.89 cm
Читательская аудитория: Professional and scholarly
Ключевые слова: Artificial intelligence,Neural networks & fuzzy systems, COMPUTERS / Intelligence (AI) & Semantics,COMPUTERS / Neural Networks
Подзаголовок: Theories, methods, and applications
Рейтинг:
Поставляется из: Англии
Описание:

Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction.

This book provides a comprehensive introduction to the basic concepts, models, and applications of network representation learning (NRL). The book starts with an introduction to the background and rising of network embeddings as a general overview for readers. Then it introduces the development of NE techniques by presenting several representative methods on general graphs, as well as a unified NE framework based on matrix factorization. Afterward, it presents the variants of NE with additional information: NE for graphs with node attributes/contents/labels; and the variants with different characteristics: NE for community-structured/large-scale/heterogeneous graphs. Further, the book introduces different applications of NE such as recommendation and information diffusion prediction. Finally, the book concludes the methods and applications and looks forward to the future directions.


Network Embedding: Theories, Methods, and Applications

Автор: Yang Cheng, Liu Zhiyuan, Tu Cunchao
Название: Network Embedding: Theories, Methods, and Applications
ISBN: 1636390463 ISBN-13(EAN): 9781636390468
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 15939.00 р.
Наличие на складе: Поставка под заказ.

Описание:

Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction.

This book provides a comprehensive introduction to the basic concepts, models, and applications of network representation learning (NRL). The book starts with an introduction to the background and rising of network embeddings as a general overview for readers. Then it introduces the development of NE techniques by presenting several representative methods on general graphs, as well as a unified NE framework based on matrix factorization. Afterward, it presents the variants of NE with additional information: NE for graphs with node attributes/contents/labels; and the variants with different characteristics: NE for community-structured/large-scale/heterogeneous graphs. Further, the book introduces different applications of NE such as recommendation and information diffusion prediction. Finally, the book concludes the methods and applications and looks forward to the future directions.
Kernel mean embedding of distributions:

Автор: Muandet, Krikamol Fukumizu, Kenji Sriperumbudur, Bharath Scholkopf, Bernhard
Название: Kernel mean embedding of distributions:
ISBN: 1680832883 ISBN-13(EAN): 9781680832884
Издательство: Неизвестно
Рейтинг:
Цена: 13656.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This monograph provides a comprehensive review of kernel mean embeddings of distributions and, in the course of doing so, discusses some challenging issues that could potentially lead to new research directions. The targeted audience includes graduate students and researchers in machine learning and statistics who are interested in the theory and applications of kernel mean embeddings.

Graph Embedding for Pattern Analysis

Автор: Yun Fu; Yunqian Ma
Название: Graph Embedding for Pattern Analysis
ISBN: 1489990623 ISBN-13(EAN): 9781489990624
Издательство: Springer
Рейтинг:
Цена: 16977.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book presents advances in graph embedding theories, such as nonlinear manifold graph, linearization method, graph based subspace analysis, L1 graph, hypergraph, undirected graph and graph in vector spaces, and describes their real-world applications.

Machine Learning in Social Networks: Embedding Nodes, Edges, Communities, and Graphs

Автор: Aggarwal Manasvi, Murty M. N.
Название: Machine Learning in Social Networks: Embedding Nodes, Edges, Communities, and Graphs
ISBN: 9813340215 ISBN-13(EAN): 9789813340213
Издательство: Springer
Цена: 9083.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Introduction

1.1 introduction

1.2 Notations used in Book

1.3 Contents covered in this book

2 Representations of Networks

2.1 Introduction

2.2 Networks Represented as Graphs

2.3 Data Structures to Represent Graphs

2.3.1 Matrix Representation

2.3.2 Adjacency List

2.4 Network Embeddings

2.5 Evaluation Datasets

2.5.1 Evaluation Datasets

2.5.2 Evaluation Metrics

2.6 Machine Learning Downstream Tasks

2.6.1 Classification

2.6.2 Clustering

2.6.3 Link Prediction (LP)

2.6.4 Visualization

2.6.5 Network Reconstruction

2.7 Embeddings based on Matrix Factorization

2.7.1 Singular Value Decomposition (SVD)

2.7.2 Matrix Factorization based Clustering

2.7.3 Soft Clustering as Matrix Factorization

2.7.4 Non-negative Matrix factorization (NMF)

2.8 Word2vec

2.8.1 Skipgram model

2.9 Learning Network Embeddings

2.9.1 Supervised Learning

2.9.2 Unsupervised Learning

2.9.3 Node and Edge Embeddings

2.9.4 Graph Embedding

2.10 Summary

3 Deep Learning

3.1 Introduction

3.2 Neural Networks

3.2.1 Perceptron

3.2.2 Characteristics of Neural Networks

3.2.3 Multilayer Perceptron Networks

3.2.4 Training MLP Networks

3.3 Convolution Neural Networks

3.3.1 Activation Function

3.3.2 Initialization of Weights

3.3.3 Deep Feedforward Neural Network

3.4 Recurrent Networks

3.4.1 Recurrent Neural Networks

3.4.2 Long Short Term Memory

3.4.3 Different Gates used by LSTM

3.4.4 Training of LSTM Models

3.5 Learning Representations using Autoencoders

3.5.1 Types of Autoencoders

3.6 Summary

References

4 Embedding Nodes and Edge

4.1 Introduction

4.2 Representation of Node and Edges as Vectors

4.3 Embeddings based on Random Walks

4.4 Embeddings based on Matrix Factorization

4.5 Graph Neural Network Models

4.6 State of the art algorithms

4.7 Evaluation methods and Machine Learning tasks

4.8 Summary

References

5 Embedding Graphs

5.1 Introduction

5.2 Representation of Graphs as Vectors

5.3 Graph Representation using Node Embeddings

5.4 Graph Pooling Techniques

5.4.1 Global Pooling Methods

5.4.2 Hierarchical Pooling Methods

5.5 State of the art algorithms

5.6 Evaluation methods and Machine Learning tasks

5.7 Summary

References
Challenges in Social Network Research: Methods and Applications

Автор: Ragozini Giancarlo, Vitale Maria Prosperina
Название: Challenges in Social Network Research: Methods and Applications
ISBN: 3030314650 ISBN-13(EAN): 9783030314651
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Some authors explore new trends related to network measures, multilevel networks and clustering on networks, while other contributions deepen the relationship among statistical methods for data mining and social network analysis.

Optoelectronics in Machine Vision-Based Theories and Applications

Автор: Moises Rivas-Lopez, Oleg Sergiyenko, Wendy Flores-Fuentes, Julio Cesar Rodriguez-Quinonez
Название: Optoelectronics in Machine Vision-Based Theories and Applications
ISBN: 1522557512 ISBN-13(EAN): 9781522557517
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 28215.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Sensor technologies play a large part in modern life, as they are present in things like security systems, digital cameras, smartphones, and motion sensors. While these devices are always evolving, research is being done to further develop this technology to help detect and analyze threats, perform in-depth inspections, and perform tracking services.Optoelectronics in Machine Vision-Based Theories and Applications provides innovative insights on theories and applications of optoelectronics in machine vision-based systems. It also covers topics such as applications of unmanned aerial vehicle, autonomous and mobile robots, medical scanning, industrial applications, agriculture, and structural health monitoring. This publication is a vital reference source for engineers, technology developers, academicians, researchers, and advanced-level students seeking emerging research on sensor technologies and machine vision.

Bio-inspired Computing – Theories and Applications

Автор: Maoguo Gong; Linqiang Pan; Tao Song; Gexiang Zhang
Название: Bio-inspired Computing – Theories and Applications
ISBN: 9811036136 ISBN-13(EAN): 9789811036132
Издательство: Springer
Рейтинг:
Цена: 12577.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The two-volume set, CCIS 681 and CCIS 682, constitutes the proceedings of the 11th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2016, held in Xi`an, China, in October 2016.The 115 revised full papers presented were carefully reviewed and selected from 343 submissions.

Advanced Intelligent Computing Theories and Applications

Автор: De-Shuang Huang; Kyungsook Han
Название: Advanced Intelligent Computing Theories and Applications
ISBN: 3319220527 ISBN-13(EAN): 9783319220529
Издательство: Springer
Рейтинг:
Цена: 13416.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book - in conjunction with the double volume LNCS 9225-9226 - constitutes the refereed proceedings of the 11th International Conference on Intelligent Computing, ICIC 2015, held in Fuzhou, China, in August 2015.

Intuitionistic Fuzziness and Other Intelligent Theories and Their Applications

Автор: Hadjiski
Название: Intuitionistic Fuzziness and Other Intelligent Theories and Their Applications
ISBN: 3319789309 ISBN-13(EAN): 9783319789309
Издательство: Springer
Рейтинг:
Цена: 16769.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book gathers extended versions of the best papers presented at the 8th IEEE conference on Intelligent Systems, held in Sofia, Bulgaria on September 4-6, 2016, which are mainly related to theoretical research in the area of intelligent systems.

Soft Computing: Theories and Applications

Автор: Ray
Название: Soft Computing: Theories and Applications
ISBN: 9811305889 ISBN-13(EAN): 9789811305887
Издательство: Springer
Рейтинг:
Цена: 20962.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The book focuses on soft computing and its applications to solve real-world problems occurring in different domains ranging from medicine and healthcare, and supply chain management to image processing and cryptanalysis.

Bio-Inspired Computing: Theories and Applications: 14th International Conference, Bic-Ta 2019, Zhengzhou, China, November 22-25, 2019, Revised Selecte

Автор: Pan Linqiang, Liang Jing, Qu Boyang
Название: Bio-Inspired Computing: Theories and Applications: 14th International Conference, Bic-Ta 2019, Zhengzhou, China, November 22-25, 2019, Revised Selecte
ISBN: 9811534144 ISBN-13(EAN): 9789811534140
Издательство: Springer
Рейтинг:
Цена: 15092.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This two-volume set (CCIS 1159 and CCIS 1160) constitutes the proceedings of the 14th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2019, held in Zhengzhou, China, in November 2019.The 122 full papers presented in both volumes were selected from 197 submissions.

Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012)

Автор: Jagdish C. Bansal; Pramod Singh; Kusum Deep; Milli
Название: Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012)
ISBN: 8132210379 ISBN-13(EAN): 9788132210375
Издательство: Springer
Рейтинг:
Цена: 32142.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The book is a collection of high quality peer reviewed research papers presented in Seventh International Conference on Bio-Inspired Computing (BIC-TA 2012) held at ABV-IIITM Gwalior, India.


ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
Есть вопрос?
Политика конфиденциальности
Помощь
Дистрибьюторы издательства "Логосфера"
О компании
Представительство в Казахстане
 
Medpublishing.ru 
   В Контакте     В Контакте Мед  Мобильная версия