MLC

Introduction to the MLC a.k.a. the Machine Learning Curse

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• + Machine learning introduction, paradigm, estimation ... [Matt]

Supervised Learning

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Good old stuff from stistics

• - logistic regression and linear regression [Bernardo (?)]
• + LDA [Rossella (?) + Simone (?)]

Good old stuf from machine learning

• + Decision trees [Matt]
• ~ Decision rules [Matt + Andrea (?)]
• - Association rules [?]

Statistical approaches

• + Bayesian classifiers [Matt]

Non parametric methods

• - KNN & friends, Locally weighted regression,

Kernel methods

• ~ SVM and Kernel methods [Matt (?) + Luigi (?) + (?)]

Unsupervised Learning

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Distributions of data

• + Feature selection and projection (PCA, ICA, ...) [Rossella (?)+ Simone]

Clustering

• + Clustering galore [Davide (?)]

Graphical models

• ~ Bayesian networks [Matt + Luigi (?)]

Non Parametric techniques

• Kernel based density estimation, ... [Rossella (?) + Luigi (?) + Simone]

Time Varying Models

• + Markov Chains [Matt + Bernardo (?) +Simone]
• + Hidden Markov Models [Matt + Simone (?)]
• - Dynamic Bayesian Networks

Learning Techniques and Methodologies

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• ~ Cross-Validation, Bootstrapping, and model evaluation [Matt (?)]
• - Adaboost, boosting and bagging ... [?]

Knowledge representation and Learning

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• - ontologies ...

Text analysis and learning

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• - text analysis, classification, relevance feedback, latent semantic [Ahmed]

Image analysis and learning

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• - Image analysis and learning