GLUT 发表于 2025-3-26 21:08:36

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lavish 发表于 2025-3-27 03:45:20

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无价值 发表于 2025-3-27 06:55:45

Simone Mocellinlligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms..978-3-030-16935-0978-3-030-16936-7Series ISSN 2190-8354 Series E-ISSN 2191-575X

microscopic 发表于 2025-3-27 11:14:52

Simone Mocellinhe core of a computational neuroscience course.Later chapters can be used as a basis for a graduate class and as asource for current research in mathematic978-1-4614-2621-9978-0-387-87708-2Series ISSN 0939-6047 Series E-ISSN 2196-9973

初次登台 发表于 2025-3-27 14:21:08

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mediocrity 发表于 2025-3-27 21:16:46

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AVANT 发表于 2025-3-28 00:54:51

Simone Mocellinhe core of a computational neuroscience course.Later chapters can be used as a basis for a graduate class and as asource for current research in mathematic978-1-4614-2621-9978-0-387-87708-2Series ISSN 0939-6047 Series E-ISSN 2196-9973

意外的成功 发表于 2025-3-28 04:21:56

ure; learning and generalization in relationships to training set size and number of free parameters; and convergence of numerical algorithms.Examines original mathematical disciplines (statistics, numerical mathematics, system theory) as they are specifically relevant to a given problem.Addresses t

专横 发表于 2025-3-28 09:37:53

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Alcove 发表于 2025-3-28 12:52:48

Simone Mocellintensions of the model in three directions: repeated games with signals (imperfect observation of moves), stochastic games where the “Big Match” is studied, and repeated games with incomplete information where we prove the cav(u) theorem of Aumann and Maschler.
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