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Learning-Based Local Visual Representation and Indexing

Learning-Based Local Visual Representation and Indexing, reviews the state-of-the-art in visual content representation and indexing;

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Representation Learning for Natural Language Processing

This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for;

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Representation Learning for Natural Language Processing

This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for;

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Logic for Learning

This book provides a systematic approach to knowledge representation, computation, and learning using higher-order logic. For those;

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Logic for Learning

This book provides a systematic approach to knowledge representation, computation, and learning using higher-order logic. For those;

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Associative Learning and Representation: An EPS Workshop for N.J. Mackintosh

a workshop on Associative Learning and Representation which was sponsored by the Experimental Psychology Society at Emmanuel College;

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Graph Representation Learning

this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings;

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Representation Learning

This monograph addresses advances in representation learning, a cutting-edge research area of machine learning. Representation learning;

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Representation Learning

This monograph addresses advances in representation learning, a cutting-edge research area of machine learning. Representation learning;

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Learning Representation for Multi-View Data Analysis

, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the;

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PassKey Learning Systems EA Review Part 3 Representation, Enrolled Agent Study Guide

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Trends in Deep Learning Methodologies

algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher;

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Robust Representation for Data Analytics

This book introduces the concepts and models of robust representation learning, and provides a set of solutions to deal with real-world;

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Deep Learning and Linguistic Representation

achievements for the modelling of human learning and representation remains unclear. Deep Learning and Linguistic Representation looks at the;

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Deep Learning and Linguistic Representation

achievements for the modelling of human learning and representation remains unclear. Deep Learning and Linguistic Representation looks at the;

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Deep Learning

This book introduces readers to the fundamental concepts of deep learning and offers practical insights into how this learning paradigm;

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Deep Learning: Concepts and Architectures

This book introduces readers to the fundamental concepts of deep learning and offers practical insights into how this learning paradigm;

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Heterogeneous Graph Representation Learning and Applications

Representation learning in heterogeneous graphs (HG) is intended to provide a meaningful vector representation for each node so as to;

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Inductive Logic Programming

submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform;

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Inductive Logic Programming

. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation;

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Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data

This book constitutes the refereed proceedings of the First MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2019;

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Researching into Student Learning and Support in Colleges and Universities

This work looks at the issues of student learning and support, in the context of their own institution. Issues covered include student;

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Researching into Student Learning and Support in Colleges and Universities

This work looks at the issues of student learning and support, in the context of their own institution. Issues covered include student;

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Machine Learning in Social Networks

This book deals with network representation learning. It deals with embedding nodes, edges, subgraphs and graphs. There is a growing;

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Coefficient of Variation and Machine Learning Applications

the metadata leading to efficient knowledge representation. It also compiles representational and classification strategies based on the CV;

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Artificial Intelligence Basics

, including searching processes, knowledge representation, machine learning, expert systems, programming, and robotics Includes separate chapters on;

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Coefficient of Variation and Machine Learning Applications

the metadata leading to efficient knowledge representation. It also compiles representational and classification strategies based on the CV;

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