CS 780/880: Probabilistic AI and Machine Learning

Tentative Schedule


Date Topic Required Readings
Optional readings
1/26 Overview Decision Making Under Uncertainty (DMUU) Chapter 1

1/28 Probabilistic models: Probability
DMUU 2.1, Murphy 2-2.2, 2.5-2.5.2, 2.8
Russell & Norvig Chapter 13, Murphy the rest of 2
2/2 Probabilistic models: Independence and exact inference DMUU 2.2-2.2.4, Murphy 10.1, 10.3, 10.5, 20.1-20.3 (without the starred parts) Russell & Norvig 14
Murphy the rest of 10 and 20
assignment due (probability)
2/4 Probabilistic models: Approximate inference DMUU 2.2.5, Murphy 20.5, 23.1-23.4, 24.1-24.2 Murphy the rest of 23 and 24
2/9 Decision problems: Utility theory DMUU 3.1 Russell & Norvig 16
Murphy 5.7
assignment due (inference)
2/11 Decision problems: Decision networks
DMUU 3.2, Murphy 10.6

2/16 Sequential problems: MDPs and Dynamic Programming DMUU 4.1 and 4.2 Russell & Norvig 17-17.3 assignment due (decision making)
2/18 Sequential problems: Structured representations and approximate dynamic programming
DMUU 4.3 and 4.5
2/23 Sequential problems: Online methods and policy search
DMUU 4.6 and 4.7
assignment due (MDPs)
2/25 State uncertainty: POMDPs and belief updating
DMUU 6.1 and 6.2
Russell & Norvig 17.4
3/1 State uncertainty: Exact solution methods
DMUU 6.3 and 6.4
coding assignment due
3/3 State uncertainty: Other offline and online methods DMUU 6.5

3/8 Multi-agent models and applications


assignment due (POMDPs)
3/10 Midterm exam


3/15 Spring Break!

3/17 Spring Break!

3/22 Reinforcement learning: The RL problem and model-based methods
DMUU 5.1-5.3

3/24
Reinforcement learning: Model free methods
DMUU 5.4

3/29 Classification: k-nn and logistic regression
Murphy 1 and 8-8.3

assignment due (RL)
3/31 Logistic and linear regression
Murphy 7-7.5 (without the starred parts)
4/5 Generative models
Murphy 3, DMUU 2.3

coding assignment due
4/7 More generative models

project topics due
4/12 Decision trees Murphy 16-16.3 Russell & Norvig  18.1-18.4 assignment due (regression)
4/14 More decision trees Murphy 16.4 and 16.6 Russell & Norvig 18.10
4/19 Classification: SVMs
Murphy 14.5
Russell & Norvig 18.9
assignment due (nonparametric methods)
4/21 Mixture models and EM Murphy 11
Russell & Norvig 20.3
4/26 Neural nets Murphy 16.5 Russell & Norvig 18.7 coding assignment due
4/28 Hidden Markov models Murphy 17.1-17.5 Russell & Norvig 15
5/3 Project presentations
Will, Tianyi,  Alec, Matheus, Connor

5/5 Project presentations
Madison, Reazul, Bahram, Andreas, Abolfazl, Estuardo

assignment due (HMMs and NNs)
5/9 Not a class day AAAI format

Final paper due (11:59pm)