EE-Learning
Partially Observable MDPs (POMDPs)
Catogry:
Computing
Subject:
Computer Science
Course:
Machine Learning
Lecture List
Partially Observable MDPs (POMDPs)
Advice for Applying Machine Learning
State-action Rewards
Generalization to Continuous States
Applications of Reinforcement Learning
Latent Semantic Indexing (LSI)
The Factor Analysis Model
Mixture of Gaussian
The Concept of Unsupervised Learning
Bayesian Statistics and Regularization
Uniform Convergence – The Case of Infinite H
Bias/variance Tradeoff
Kernels
Optimal Margin Classifier
Multinomial Event Model
Discriminative Algorithms
Newtons Method
The Concept of Underfitting and Overfitting
An Application of Supervised Learning – Autonomous Deriving
introduction,The Motivation Applications of Machine Learning