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  • Supervised Learning: Decision trees, nearest neighbors, linear classifiers and kernels, neural networks, linear regression; learning theory; bagging and boosting; feature selection.
  • Unsupervised Learning: Clustering, graphical models, EM, PCA, factor analysis, manifold learning.
  • Reinforcement Learning: Value iteration; policy iteration; TD learning; Q learning; actor-critic.
  • Other Topics: Bayesian learning, online learning.
posted on 2008-04-27 20:22 Bati 阅读(...) 评论(...) 编辑 收藏