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

Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent, Zhou Jianlong, Chen Fang


Варианты приобретения
Цена: 9083.00р.
Кол-во:
Наличие: Поставка под заказ.  Есть в наличии на складе поставщика.
Склад Америка: Есть  
При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября
При условии наличия книги у поставщика.

Добавить в корзину
в Мои желания

Автор: Zhou Jianlong, Chen Fang
Название:  Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent
ISBN: 9783030080075
Издательство: Springer
Классификация:



ISBN-10: 3030080072
Обложка/Формат: Paperback
Страницы: 482
Вес: 0.70 кг.
Дата издания: 10.01.2019
Серия: Human-computer interaction series
Язык: English
Издание: Softcover reprint of
Иллюстрации: 114 illustrations, color; 26 illustrations, black and white; xxiii, 482 p. 140 illus., 114 illus. in color.
Размер: 234 x 156 x 26
Читательская аудитория: General (us: trade)
Подзаголовок: Visible, explainable, trustworthy and transparent
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of “black-box” in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications.This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making.This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially benefit researchers in areas like artificial intelligence, decision support systems and human-computer interaction.
Дополнительное описание: Part I Transparency in Machine Learning.- Part II Visual Explanation of Machine Learning Process.- Part III Algorithmic Explanation of Machine Learning Models.- Part IV User Cognitive Responses in ML-Based Decision Making.- Part V Human and Evaluation of



Trustworthy Ubiquitous Computing

Автор: Ismail Khalil; Teddy Mantoro
Название: Trustworthy Ubiquitous Computing
ISBN: 9462390576 ISBN-13(EAN): 9789462390577
Издательство: Springer
Рейтинг:
Цена: 13275.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Trustworthy Ubiquitous Computing covers aspects of trust in ubiquitous computing environments.

Trustworthy Open Self-Organising Systems

Автор: Reif
Название: Trustworthy Open Self-Organising Systems
ISBN: 3319291998 ISBN-13(EAN): 9783319291994
Издательство: Springer
Рейтинг:
Цена: 13275.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This booktreats the computational use of social concepts as the focal point for therealisation of a novel class of socio-technical systems, comprising smartgrids, public display environments, and grid computing.Thesesystems are composed of technical and human constituents that interact witheach other in an open environment. Heterogeneity, large scale, and uncertaintyin the behaviour of the constituents and the environment are the rule ratherthan the exception.Ensuringthe trustworthiness of such systems allows their technical constituents tointeract with each other in a reliable, secure, and predictable way while theirhuman users are able to understand and control them. 'TrustworthyOpen Self-Organising Systems' contains a wealth of knowledge, fromtrustworthy self-organisation mechanisms, to trust models, methods to measure auser's trust in a system, a discussion of social concepts beyond trust, andinsights into the impact open self-organising systems will have on society.

Trustworthy Eternal Systems via Evolving Software, Data and Knowledge

Автор: Alessandro Moschitti; Barbara Plank
Название: Trustworthy Eternal Systems via Evolving Software, Data and Knowledge
ISBN: 3642452590 ISBN-13(EAN): 9783642452598
Издательство: Springer
Рейтинг:
Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the thoroughly refereed proceedings of the Second International Workshop on Trustworthy Eternal Systems via Evolving Software, Data and Knowledge, EternalS, held in Montpellier, France, in August 2012 and co-located with the 20th European Conference on Artificial Intelligence (ECAI 2012).

Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems

Автор: Mar Marcos; Jose M. Juarez; Richard Lenz; Grzegorz
Название: Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems
ISBN: 3030374459 ISBN-13(EAN): 9783030374457
Издательство: Springer
Рейтинг:
Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes revised selected papers from the AIME 2019 workshops KR4HC/ProHealth 2019, the Workshop on Knowledge Representation for Health Care and Process-Oriented Information Systems in Health Care, and TEAAM 2019, the Workshop on Transparent, Explainable and Affective AI in Medical Systems.

Explainable, Transparent Autonomous Agents and Multi-Agent Systems

Автор: Davide Calvaresi; Amro Najjar; Michael Schumacher;
Название: Explainable, Transparent Autonomous Agents and Multi-Agent Systems
ISBN: 303030390X ISBN-13(EAN): 9783030303907
Издательство: Springer
Рейтинг:
Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the proceedings of the First International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems, EXTRAAMAS 2019, held in Montreal, Canada, in May 2019. The 12 revised and extended papers presented were carefully selected from 23 submissions. explainable agent simulations;

Explainable and Interpretable Models in Computer Vision and Machine Learning

Автор: Hugo Jair Escalante; Sergio Escalera; Isabelle Guy
Название: Explainable and Interpretable Models in Computer Vision and Machine Learning
ISBN: 3319981307 ISBN-13(EAN): 9783319981307
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning.Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: · Evaluation and Generalization in Interpretable Machine Learning· Explanation Methods in Deep Learning· Learning Functional Causal Models with Generative Neural Networks· Learning Interpreatable Rules for Multi-Label Classification· Structuring Neural Networks for More Explainable Predictions· Generating Post Hoc Rationales of Deep Visual Classification Decisions· Ensembling Visual Explanations· Explainable Deep Driving by Visualizing Causal Attention· Interdisciplinary Perspective on Algorithmic Job Candidate Search· Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions · Inherent Explainability Pattern Theory-based Video Event Interpretations
Reasoning Web. Explainable Artificial Intelligence

Автор: Markus Kr?tzsch; Daria Stepanova
Название: Reasoning Web. Explainable Artificial Intelligence
ISBN: 3030314227 ISBN-13(EAN): 9783030314224
Издательство: Springer
Рейтинг:
Цена: 8104.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This volume contains lecture notes of the 15th Reasoning Web Summer School (RW 2019), held in Bolzano, Italy, in September 2019. The research areas of Semantic Web, Linked Data, and Knowledge Graphs have recently received a lot of attention in academia and industry. Since its inception in 2001, the Semantic Web has aimed at enriching the existing Web with meta-data and processing methods, so as to provide Web-based systems with intelligent capabilities such as context awareness and decision support. The Semantic Web vision has been driving many community efforts which have invested a lot of resources in developing vocabularies and ontologies for annotating their resources semantically. Besides ontologies, rules have long been a central part of the Semantic Web framework and are available as one of its fundamental representation tools, with logic serving as a unifying foundation. Linked Data is a related research area which studies how one can make RDF data available on the Web and interconnect it with other data with the aim of increasing its value for everybody. Knowledge Graphs have been shown useful not only for Web search (as demonstrated by Google, Bing, etc.) but also in many application domains.

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning

Автор: Wojciech Samek; Gr?goire Montavon; Andrea Vedaldi;
Название: Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
ISBN: 3030289532 ISBN-13(EAN): 9783030289539
Издательство: Springer
Рейтинг:
Цена: 10340.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner.The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Transparent Urban Development

Автор: Benjamin W. Stanley
Название: Transparent Urban Development
ISBN: 3319589091 ISBN-13(EAN): 9783319589091
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Utilizing mixed research methods to probe downtown Phoenix`s political economy of development, this study illustrates how non-local property ownership and land speculation negatively impacted a concerted public-private effort to encourage infill construction on vacant land.

Engineering Trustworthy Software Systems

Автор: Jonathan P. Bowen; Zhiming Liu; Zili Zhang
Название: Engineering Trustworthy Software Systems
ISBN: 3030176002 ISBN-13(EAN): 9783030176006
Издательство: Springer
Рейтинг:
Цена: 8104.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This volume contains lectures on leading-edge research in methods and tools for use in computer system engineering;

Transparent User Authentication

Автор: Nathan Clarke
Название: Transparent User Authentication
ISBN: 1447160118 ISBN-13(EAN): 9781447160113
Издательство: Springer
Рейтинг:
Цена: 15372.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This groundbreaking book introduces and examines the technology required to implement transparent user authentication, in which credentials are captured in the user`s normal interaction with a system. Covers novel behavioural biometrics techniques and more.


ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
   В Контакте     В Контакте Мед  Мобильная версия