Computer Science 246/446

Machine Learning

Spring 2025

Instructor: Dan Gildea office hours T/Th 2-3pm, 3019 Wegmans

TAs: Zhenghong Zhou, office hours Fri 4-5pm, 3504 Wegmans
Daoan Zhang, office hours Mon 9-10am, 3504 Wegmans

Prereqs: Probability, Linear Algebra, Vector Calculus.

Homeworks

Lecture notes

Required text: Christopher M. Bishop, Pattern Recognition and Machine Learning.

The following are useful references in addition to the reading material assigned for each class:

  • Stuart Russell and Peter Norvig, Artificial Intelligence, A Modern Approach.
  • Trevor Hastie, Robert Tibshirani, Jerome Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction.
  • Larry Wasserman, All of Statistics, 2004.

Syllabus

Onwe will coverwhich means that after class you will understandif before class you have read
1/21 Regression and Classification perceptron, linear regression bishop 1.2, 1.4, app E
1/23 Logistic Regression stochastic gradient descent bishop 4.3
1/28 Convexity positive semidefinite matrices
1/30 Backpropagation DP for gradient descent bishop 5.1, 5.2, 5.3, Krizhevsky 2012
2/4 Support Vectors max-margin bishop 3.1, 4.1
2/6 Support Vectors strong duality bishop 7.1
2/11 Support Vectors the kernel trick bishop 6.1, 6.2
2/13 Hidden Markov Models forward-backward bishop 13.2
2/18 Graphical Models bayes ball
2/20 Probabilistic Inference message passing bishop 8.4
2/25 Tree decomposition cyclic graphs koller and friedman
2/27 Tree decomposition cont'd vertex elimination
3/4 Review
3/6 Midterm
3/18 Midterm Solutions
3/20 Fairness in machine learning Kleinberg, Corbett-Davies
3/25 Expectation Maximization mixture of gaussians bishop 9
3/27 Expectation Maximization L = Q + H + D bishop 9
4/1 EM for HMM minimum bayes risk
4/3 Sampling Markov Chain Monte Carlo bishop 11.2
4/8 Metropolis Hastings detailed balance bishop 11.2
4/10 Gibbs sampling annealing bishop 11.3
4/15 no class
4/17 Transformers deep generative models
4/22 Gradient Descent SGD convergence Ruder 2016
4/24 Reinforcement Learning q-learning sutton ch 3, 4.3, 4.4, 6.1, 6.5, 7.2, 11.1
4/29 Something fun VAE, Diffusion Kingma and Welling 2014, Ho et al. 2020
5/1 Review come to class with questions!
Final exam: Th May 8, 7:15-10:15pm, in classroom.

Grading

  • Homeworks: 50%
  • Final exam: 30%
  • Midterm: 20%

gildea @ cs rochester edu
March 27, 2025