Lectures

Tuesday & Thursday, 2:30pm-3:50pm, Smith-Buonanno Hall 106.

Most primary readings come from Bishop's Pattern Recognition and Machine Learning (PRML). Available at the Brown Bookstore.
Some readings come from Hastie, Tibshirani, & Friedman's Elements of Statistical Learning (ESL). Available online.


Date Topics Primary Reading Supplemental Reading Materials
September 10 Introduction slides
September 15 Classification and Nearest Neighbors

PRML: 1.1, 1.4, 2.5

ESL: 2.1-2.3, 2.5

slides
September 17 Generative Models and Decision Theory

PRML: 1.2, 1.3, 1.5

ESL: 2.4

slides
September 22 Directed Graphical Models

PRML: 8.1-8.2

slides
September 24 Frequentist Learning and Naive Bayes

PRML: 2.1-2.2

ESL: 8.2

slides
September 29 Bayesian Learning and Naive Bayes

PRML: 2.1-2.2

ESL: 8.3

slides
October 1 Bayesian Learning and Continuous Decisions

PRML: 1.5, 2.3

slides
October 6 Generative Gaussian Classification

PRML: 2.3, 4.2

slides
October 8 Multivariate Gaussian Distributions

PRML: 2.3, C

slides
October 13 Discriminative Linear Regression

PRML: 3.1-3.3

ESL: 3.2, 3.4

slides
October 15 Discriminative Logistic Regression

PRML: 4.1, 4.3

ESL: 4.1-4.4

slides
October 20 Discriminative Learning via Gradient Descent PRML: 4.3, 5.2 slides
October 22 Feature Induction and Neural Networks PRML: 5.1-5.3, 5.5 ESL: 11 slides
October 27 Feature Selection and L1 Regularization ESL: 3.2-3.4 slides
October 29 Sparsity and Kernels PRML: 6.1-6.2 slides, string kernels
November 3 Gaussian Process Regression and Classification PRML: 6.4 slides
November 5 Support Vector Machines, Decision Trees PRML: 7.1, 14.4 ESL: 12.2-12.3 slides
November 10 Clustering and the K-Means Algorithm PRML: 9.1-9.2 ESL: 13.2, 14.3 slides
November 12 Mixture Models and the EM Algorithm PRML: 9.3-9.4 slides
November 17 Hidden Markov Models: Viterbi Algorithm PRML: 13.1-13.2 slides
November 19 Hidden Markov Models: Forward-Backward and EM PRML: 13.2 slides
November 24 Principal Components Analysis PRML: 12.1 ESL: 14.5 slides
November 26 THANKSGIVING
December 1 Factor Analysis and the EM Algorithm PRML: 12.2 slides
December 3 Review and Advanced Topics PRML: 13.3 slides
December 8 READING PERIOD (FINAL)
December 10 READING PERIOD (FINAL)