Representation in Machine Learning, Murty

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 1493938436 ISBN-13(EAN): 9781493938438
Издательство: Springer
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Цена: 69870.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Название: Mathematics for Machine Learning
ISBN: 110845514X ISBN-13(EAN): 9781108455145
Издательство: Cambridge Academ
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Цена: 42230.00 T
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Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.

Автор: Meliot, Pierre-Loic
Название: Representation Theory of Symmetric Groups
ISBN: 1032476923 ISBN-13(EAN): 9781032476926
Издательство: Taylor&Francis
Рейтинг:
Цена: 46950.00 T
Наличие на складе: Нет в наличии.
Описание: Representation Theory of Symmetric Groups is the most up-to-date abstract algebra book on the subject of symmetric groups and representation theory. Utilizing new research and results, this book can be studied from a combinatorial, algorithmic or algebraic viewpoint. This book is an excellent way of introducing today's students to representation theory of the symmetric groups, namely classical theory.

From there, the book explains how the theory can be extended to other related combinatorial algebras like the Iwahori-Hecke algebra. In a clear and concise manner, the author presents the case that most calculations on symmetric group can be performed by utilizing appropriate algebras of functions. Thus, the book explains how some Hopf algebras (symmetric functions and generalizations) can be used to encode most of the combinatorial properties of the representations of symmetric groups.

Overall, the book is an innovative introduction to representation theory of symmetric groups for graduate students and researchers seeking new ways of thought.

Автор: Mailund Thomas
Название: String Algorithms in C: Efficient Text Representation and Search
ISBN: 148425919X ISBN-13(EAN): 9781484259191
Издательство: Springer
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Цена: 60550.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 1. Introduction.- 2. Classical Algorithms for Exact Search 3. Suffix Trees4. Suffix Arrays 5. Approximate Search6. ConclusionsAppendix A: VectorsAppendix B: ListsAppendix C: Queues

Автор: Hamilton, William L.
Название: Graph Representation Learning
ISBN: 3031004604 ISBN-13(EAN): 9783031004605
Издательство: Springer
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Цена: 51230.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis.This book provides a synthesis and overview of graph representation learning.

Автор: Katharina Morik
Название: Knowledge Representation and Organization in Machine Learning
ISBN: 354050768X ISBN-13(EAN): 9783540507680
Издательство: Springer
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Цена: 51230.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning has become a growing field of Artificial Intelligence. This book contains research papers that focus on the relation between knowledge representation, knowledge acquisition and machine learning from a different angle. It is of interest to both experts and newcomers to the subject.

Автор: Kumar Avadhesh, Sagar Shrddha, Kumar T. Ganesh
Название: Prediction and Analysis for Knowledge Representation and Machine Learning
ISBN: 0367649101 ISBN-13(EAN): 9780367649104
Издательство: Taylor&Francis
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Цена: 137810.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book illustrates different techniques and structures that are used in knowledge representation and machine learning. The aim of this book is to draw the attention of graduates, researchers and practitioners working in field of information technology and computer science (in knowledge representation in machine learning).

Автор: Zhengming Ding; Handong Zhao; Yun Fu
Название: Learning Representation for Multi-View Data Analysis
ISBN: 3030007332 ISBN-13(EAN): 9783030007331
Издательство: Springer
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Цена: 111790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers’ understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal.A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.

Автор: Bergman, Michael K.
Название: A knowledge representation practionary
ISBN: 3319980912 ISBN-13(EAN): 9783319980911
Издательство: Springer
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Цена: 186330.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

This major work on knowledge representation is based on the writings of Charles S. Peirce, a logician, scientist, and philosopher of the first rank at the beginning of the 20th century. This book follows Peirce's practical guidelines and universal categories in a structured approach to knowledge representation that captures differences in events, entities, relations, attributes, types, and concepts. Besides the ability to capture meaning and context, the Peircean approach is also well-suited to machine learning and knowledge-based artificial intelligence. Peirce is a founder of pragmatism, the uniquely American philosophy.

Knowledge representation is shorthand for how to represent human symbolic information and knowledge to computers to solve complex questions. KR applications range from semantic technologies and knowledge management and machine learning to information integration, data interoperability, and natural language understanding. Knowledge representation is an essential foundation for knowledge-based AI.

This book is structured into five parts. The first and last parts are bookends that first set the context and background and conclude with practical applications. The three main parts that are the meat of the approach first address the terminologies and grammar of knowledge representation, then building blocks for KR systems, and then design, build, test, and best practices in putting a system together. Throughout, the book refers to and leverages the open source KBpedia knowledge graph and its public knowledge bases, including Wikipedia and Wikidata. KBpedia is a ready baseline for users to bridge from and expand for their own domain needs and applications. It is built from the ground up to reflect Peircean principles.

This book is one of timeless, practical guidelines for how to think about KR and to design knowledge management (KM) systems. The book is grounded bedrock for enterprise information and knowledge managers who are contemplating a new knowledge initiative.

This book is an essential addition to theory and practice for KR and semantic technology and AI researchers and practitioners, who will benefit from Peirce's profound understanding of meaning and context.

Автор: David Ria?o; Richard Lenz; Silvia Miksch; Mor Pele
Название: Knowledge Representation for Health Care
ISBN: 3319265849 ISBN-13(EAN): 9783319265841
Издательство: Springer
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Цена: 37270.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This Top-Up Launchpack is ideal for those who already have the Early Level 1 Launchpack containing Sets A and B. This pack completes the set with 6 copies each of all 16 New Early Level 1 Set C Titles: Blow Wind Blow, Busy Buddy, Going to Ski, Faces Show Feelings, Help Me Please, Make a Snowman, Sand Everywhere! What Will We Eat?, Collections, Endangered Animals, Hats on Heads, Heavy or Light?, High, Higher, Highest, Pairs of Feet, This or That?, Where Do Animals Sleep?Packaged in a single carry case with divider cards.

Автор: Цzзep Цzgьr Lьtfь
Название: Representation Theorems in Computer Science: A Treatment in Logic Engineering
ISBN: 3030257878 ISBN-13(EAN): 9783030257873
Издательство: Springer
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Цена: 93160.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 1 Introduction.- 2 Preliminaries.- 3 Representing Spatial Relatedness.- 4 Scalable Spatio-Thematic Query Answering.- 5 Representation Theorems for Stream Processing.- 6 High-Level Declarative Stream Processing.- 7 Representation for Belief Revision.- 8 Conclusion.

Автор: Shyamanta M. Hazarika
Название: Qualitative Spatio-Temporal Representation and Reasoning: Trends and Future Directions
ISBN: 1616928689 ISBN-13(EAN): 9781616928681
Издательство: Mare Nostrum (Eurospan)
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Цена: 189420.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides a contribution to the emerging discipline of qualitative spatial information theory within artificial intelligence. It covers both theory and application-centric research in the area of qualitative spatial and temporal reasoning and provides a comprehensive perspective on the emerging area of qualitative spatio-temporal representation and reasoning.