Foundations of Machine Learning

and Data Mining @TUHH 2013

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Rainer Marrone, Ralf Möller

What‘s missing?

Knowledge in Learning (AIMA Ch. 19) Learning based on first-order logic Learning based on first-order probabilistic logic (e.g., PRMs)

Learning for continuous models (AIMA Ch. 20) Gaussian ML (20.2.3/4) Density estimation with nonparametric models only sketched

(20.2.6) Mixture of Gaussians (20.3.1)

Learning Hidden Markov Models or Dynamic Bayesian Networks (20.3.3) But see Reinforcement Learning

Some techniques only sketched ... e.g., Neural networks e.g., Support vector machines (SVMs)

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Further Reading

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Further Reading

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