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A systematic review of the application of computational grounded theory method in healthcare research. [PDF]
Biol Methods ProtocShankar R, Devi F, Qian X.
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Cognitive salience features enhance multitask deep learning for pragmatic reasoning across cultures. [PDF]
Sci RepQi M, Thai YN.
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Algorithms and Theory of Computation Handbook, 2015
As they say, nothing is more practical than a good theory. And indeed, mathematical models of learnability have helped improve our understanding of what it takes to induce a useful classifier from data, and, conversely, why the outcome of a machine-learning undertaking so often disappoints.
E. Xing
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As they say, nothing is more practical than a good theory. And indeed, mathematical models of learnability have helped improve our understanding of what it takes to induce a useful classifier from data, and, conversely, why the outcome of a machine-learning undertaking so often disappoints.
E. Xing
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Elements of Computational Learning Theory
Neural Networks and Statistical Learning, 2019PAC learning theory is the foundation of computational learning theory. VC-dimension, Rademacher complexity, and empirical risk-minimization principle are three concepts for deriving a generalization error bound for a trained machine. The fundamental theorem of learning theory relates PAC learnability, VC-dimension, and empirical risk-minimization ...
Ke-Lin Du, M. Swamy
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Remarks on computational learning theory
Annals of Mathematics and Artificial Intelligence, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
György Turán
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An Introduction to Computational Learning Theory
, 1994Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics.
Michael Kearns, U. Vazirani
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Computational Learning Theory and Language Acquisition
, 2012Computational learning theory explores the limits of learnability. Studying language acquisition from this perspective involves identifying classes of languages that are learnable from the available data, within the limits of time and computational resources available to the learner.
Alexander Clark, Shalom Lappin
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