Librería: ThriftBooks-Atlanta, AUSTELL, GA, Estados Unidos de America
EUR 19,67
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Añadir al carritoPaperback. Condición: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
Publicado por Morgan & Claypool Publishers, 2014
ISBN 10: 1627050876 ISBN 13: 9781627050876
Idioma: Inglés
Librería: suffolkbooks, Center moriches, NY, Estados Unidos de America
EUR 16,11
Cantidad disponible: 2 disponibles
Añadir al carritopaperback. Condición: Very Good. Fast Shipping - Safe and Secure 7 days a week!
Publicado por Morgan & Claypool Publishers, 2014
ISBN 10: 1608459675 ISBN 13: 9781608459674
Idioma: Inglés
Librería: suffolkbooks, Center moriches, NY, Estados Unidos de America
EUR 30,62
Cantidad disponible: 7 disponibles
Añadir al carritopaperback. Condición: Very Good. Fast Shipping - Safe and Secure 7 days a week!
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 32,13
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Añadir al carritoCondición: As New. Unread book in perfect condition.
EUR 32,16
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EUR 32,56
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Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 31,08
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 33,41
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Añadir al carritoCondición: New.
EUR 31,08
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
EUR 34,11
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EUR 34,37
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Añadir al carritoCondición: As New. Unread book in perfect condition.
EUR 34,41
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Añadir al carritoCondición: New.
EUR 34,53
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Añadir al carritoCondición: As New. Unread book in perfect condition.
EUR 32,98
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
EUR 35,36
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Añadir al carritoCondición: New.
EUR 32,98
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
EUR 32,98
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
EUR 36,37
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EUR 36,63
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EUR 37,52
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Publicado por Springer International Publishing AG, CH, 2020
ISBN 10: 3031004604 ISBN 13: 9783031004605
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 39,89
Cantidad disponible: Más de 20 disponibles
Añadir al carritoPaperback. Condición: New. Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. 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. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs-a nascent but quickly growing subset of graph representation learning.
Publicado por Springer International Publishing AG, CH, 2014
ISBN 10: 3031004396 ISBN 13: 9783031004391
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 39,94
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: New. 1°. Solving challenging computational problems involving time has been a critical component in the development of artificial intelligence systems almost since the inception of the field. This book provides a concise introduction to the core computational elements of temporal reasoning for use in AI systems for planning and scheduling, as well as systems that extract temporal information from data. It presents a survey of temporal frameworks based on constraints, both qualitative and quantitative, as well as of major temporal consistency techniques. The book also introduces the reader to more recent extensions to the core model that allow AI systems to explicitly represent temporal preferences and temporal uncertainty. This book is intended for students and researchers interested in constraint-based temporal reasoning. It provides a self-contained guide to the different representations of time, as well as examples of recent applications of time in AI systems.
Publicado por Springer International Publishing AG, CH, 2017
ISBN 10: 3031004485 ISBN 13: 9783031004483
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 39,94
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: New. 1°. Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of more severe side effects. In this book, we outline how to deal with multiple objectives in decision-theoretic planning and reinforcement learning algorithms. To illustrate this, we employ the popular problem classes of multi-objective Markov decision processes (MOMDPs) and multi-objective coordination graphs (MO-CoGs).First, we discuss different use cases for multi-objective decision making, and why they often necessitate explicitly multi-objective algorithms. We advocate a utility-based approach to multi-objective decision making, i.e., that what constitutes an optimal solution to a multi-objective decision problem should be derived from the availableinformation about user utility. We show how different assumptions about user utility and what types of policies are allowed lead to different solution concepts, which we outline in a taxonomy of multi-objective decision problems.Second, we show how to create new methods for multi-objective decision making using existing single-objective methods as a basis. Focusing on planning, we describe two ways to creating multi-objective algorithms: in the inner loop approach, the inner workings of a single-objective method are adapted to work with multi-objective solution concepts; in the outer loop approach, a wrapper is created around a single-objective method that solves the multi-objective problem as a series of single-objective problems. After discussing the creation of such methods for the planning setting, we discuss how these approaches apply to the learning setting.Next, we discuss three promising application domains for multi-objective decision making algorithms: energy, health, and infrastructure and transportation. Finally, we conclude by outlining important open problems and promising future directions.
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 40,31
Cantidad disponible: 5 disponibles
Añadir al carritoPaperback or Softback. Condición: New. Active Learning. Book.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 37,21
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 37,21
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 37,21
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 37,21
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 37,55
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Publicado por Springer International Publishing AG, CH, 2014
ISBN 10: 303100440X ISBN 13: 9783031004407
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 44,28
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: New. 1°. Judgment aggregation is a mathematical theory of collective decision-making. It concerns the methods whereby individual opinions about logically interconnected issues of interest can, or cannot, be aggregated into one collective stance. Aggregation problems have traditionally been of interest for disciplines like economics and the political sciences, as well as philosophy, where judgment aggregation itself originates from, but have recently captured the attention of disciplines like computer science, artificial intelligence and multi-agent systems. Judgment aggregation has emerged in the last decade as a unifying paradigm for the formalization and understanding of aggregation problems. Still, no comprehensive presentation of the theory is available to date. This Synthesis Lecture aims at filling this gap presenting the key motivations, results, abstractions and techniques underpinning it. Table of Contents: Preface / Acknowledgments / Logic Meets Social Choice Theory / Basic Concepts /Impossibility / Coping with Impossibility / Manipulability / Aggregation Rules / Deliberation / Bibliography / Authors' Biographies / Index.