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Principled Machine Learning
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AI
DOI：10.1109/JSTQE.2022.3186798.png)
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摘要
En 中文
We introduce the underlying concepts which give rise to some of the commonly usedmachine learning methods, excluding deep-learning machines and neural networks. We point to their advantages, limitations and potential use in various areas of photonics. The main methods covered include parametric and nonparametric regression and classification techniques, kernel-based methods and support vector machines, decision trees, probabilistic models, Bayesian graphs, mixture models, Gaussian processes, message passing methods and visual informatics.
Keyword:
Statistical machine learning
kernel-based methods
probabilistic methods
deciion trees
message passing techniques
dimensionality reduction
visual informatics
期刊
I
IF:
5.1
论文数:
5.6K
被引数:
1.2W
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