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Computational Learning Theory & Natural Learning Systems V 2 - Intersections Between Theory & Experiment

areas of learning research, computational learning theory, neural network research and symbolic machine learning.;

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Computational Learning Theory and Natural Learning Systems: Selecting Good Models

of three historically distinct areas of learning research: computational learning theory, neural networks andAI machine learning. Although each;

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An Introduction to Computational Learning Theory

in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics.

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Intelligent Computing Theories

, knowledge discovery and data mining, evolutionary learning and genetic algorithms machine learning theory and methods, natural language processing;

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Algorithmic Learning Theory

complexity; computational learning theory and algorithms; statistical learning theory and sample complexity; online learning, stochastic optimization;

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Experimental and Theoretical Approaches to Actinide Chemistry

current and future computational chemistry and materials techniques. In addition, the authors explore the combination of experiment and theory;

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Intersections of Formal and Informal Science

Science learning that takes place between and at the intersections of formal and informal science environments has not been systematically;

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Intersections of Formal and Informal Science

Science learning that takes place between and at the intersections of formal and informal science environments has not been systematically;

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Learning Control

Learning Control: Applications in Robotics and Complex Dynamical Systems provides a foundational understanding of control theory while also;

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Machine Learning and Systems Engineering

, Optimization algorithms, Experiment designs, Complex system identification, Computational modeling, and industrial applications. Machine Learning and;

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Intelligent Computing Theories and Technology

mining; machine learning theory and methods; biomedical informatics theory and methods; complex systems theory and methods; natural language;

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Multi-disciplinary Trends in Artificial Intelligence

, computational intelligence, game theory, machine learning, multi-agent systems, natural language, representation and reasoning, data mining, speech;

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Multi-disciplinary Trends in Artificial Intelligence

, computational philosophy, computational intelligence, game theory, machine learning, multi-agent systems, natural language, representation and reasoning;

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Multi-disciplinary Trends in Artificial Intelligence

including cognitive science; computational intelligence; computational philosophy; game theory; machine learning; multi-agent systems; natural;

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An Introduction to Natural Computation

Introduction to Natural Computation is that ideas from diverse areas such as neuroscience, information theory, and optimization theory have recently;

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An Introduction to Natural Computation

Introduction to Natural Computation is that ideas from diverse areas such as neuroscience, information theory, and optimization theory have recently;

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Systems That Learn

Formal learning theory is one of several mathematical approaches to the study of intelligent adaptation to the environment. The analysis;

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Evolution in Computational Intelligence

in Computational Intelligence (Volume 1) and Intelligent Data Engineering and Analytics (Volume 2). Covering a broad range of topics in computational;

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Mathematical Perspectives on Neural Networks

-series analysis, Bayesian analysis, regularization theory, information theory, computational learning theory, and mathematical statistics;

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Mathematical Perspectives on Neural Networks

-series analysis, Bayesian analysis, regularization theory, information theory, computational learning theory, and mathematical statistics;

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Structures and Dynamics of Autopoietic Organizations

Steffen Blaschke reconsiders the three major concepts knowledge, learning, and memory in the light of social systems theory. He complements;

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Deep Learning with TensorFlow 2 and Keras

Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key;

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Conical Intersections: Theory, Computation And Experiment

basic theoretical concepts, novel computational strategies as well as innovative experiments. The contents and discussions will be of value to;

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Cellular Automata Theory And Experiment

Cellular automata, dynamic systems in which space and time are discrete, are yielding applications in both the physical and natural;

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Systems, Self-Organisation and Information

covered, discussing the complex dynamics of living beings and the brain, and self-organized adaptation and learning in computational systems. The;

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Systems, Self-Organisation and Information

covered, discussing the complex dynamics of living beings and the brain, and self-organized adaptation and learning in computational systems. The;

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Graph Theory

; the algebraic structure of graphs; the combination of graph theory and unsupervised learning applied to social data mining; organising and;

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