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vincent-nelson
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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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