Wednesday, August 10, 2016

Slides: Lisbon Machine Learning School, LXMLS 2016

Here are the slides of Lisbon Machine Learning School, (LXMLS 2016):

LECTURE 1: Introduction to Machine Learning: Linear Learners by Stefan Riezler 
  • Feature representations and linear decision boundaries
  • Naive Bayes, logistic regression, perceptron, SVMs
  • Online learning
  • Linear learning of non-linear models
LECTURE 2: Sequence Models by Noah Smith 
  • Markov models and hidden Markov models (HMMs)
  • Dynamic programming algorithms (Viterbi and sum-product)
  • Parameter learning (MLE and Baum-Welch/EM)
  • Finite state machines and finite state transducers
  • From HMMs to CRFs: discriminative learning and features
  • Structured perceptron, structured SVMs and max-margin Markov networks
  • Training and optimization
  • Iterative scaling, L-BFGS, perceptron, MIRA, stochastic and batch gradient descent
LECTURE 4: Syntax and Parsing (III) Slav Petrov 
  • Context-free grammars (CFGs) and phrase-based parsing
  • Dynamic programming and CKY algorithm
  • Probabilistic CFGs, parent annotation and lexicalization
  • Dependency parsing (projective and non-projective)
  • Transition and graph-based parsers

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