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Titlebook: A Matrix Algebra Approach to Artificial Intelligence; Xian-Da Zhang Book 2020 Springer Nature Singapore Pte Ltd. 2020 Matrix Algebra.Artif

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樓主: minutia
11#
發(fā)表于 2025-3-23 13:26:40 | 只看該作者
Xian-Da ZhangProposes the machine learning tree, the neural network tree and the evolutionary computation tree.Presents the solid matrix algebra theory and methods for machine learning, neural networks, support ve
12#
發(fā)表于 2025-3-23 14:51:15 | 只看該作者
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13#
發(fā)表于 2025-3-23 20:03:56 | 只看該作者
14#
發(fā)表于 2025-3-24 01:23:09 | 只看該作者
The 2013 Pew Report Through a Gender Lense and gradient) is an important operation tool in matrix algebra and optimization in machine learning, neural networks, support vector machine and evolutional computation. This chapter is concerned with the theory and methods of matrix differential.
15#
發(fā)表于 2025-3-24 05:00:57 | 只看該作者
https://doi.org/10.1007/978-981-15-2770-8Matrix Algebra; Artificial Intelligence; Linear Algebra; Machine Learning; Neural Networks; Evolutionary
16#
發(fā)表于 2025-3-24 07:06:50 | 只看該作者
17#
發(fā)表于 2025-3-24 13:09:49 | 只看該作者
18#
發(fā)表于 2025-3-24 16:37:07 | 只看該作者
19#
發(fā)表于 2025-3-24 21:04:12 | 只看該作者
The 2013 Pew Report Through a Gender Lension. Optimization theory mainly considers (1) the existence conditions for an extremum value (gradient analysis); (2) the design of optimization algorithms and convergence analysis. This chapter focuses on convex optimization theory and methods by focusing on gradient/subgradient methods in smooth a
20#
發(fā)表于 2025-3-25 00:07:08 | 只看該作者
https://doi.org/10.1007/978-3-319-24505-8ethods in machine learning including single-objective optimization, feature selection, principal component analysis, and canonical correlation analysis together with supervised, unsupervised, and semi-supervised learning and active learning. More importantly, this chapter highlights selected topics
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