ECS 256 Topic Outline and Reading List
This list may be overly optimistic. We will definitely get through HMMs and
Queuing, hopefully more.
Notation:
-
"PSB" means "Probability and statistics book," ECS 256 version --
BE SURE YOU ARE USING THIS VERSION OF THE BOOK, rather than, say
the ECS 132 version or the ones for ECS 256 in previous years. Available
here.
(Note: published version
lacks some chapters that we have here.)
- "SRC" means
my book,
Statistical Regression and Classificaton: from
Linear Models to Machine Learning.
This book is NOT required, but
excerpts will be put online for you.
- "RecSys" means
my recommender systems book (work in progress)
General preparation:
- Review of undergraduate probability, PSB Chapter 10.
- Linear algebra, PSB Appendix B.
- A cautionary tale, PSB Section 5.1.
- Conditional expectation as a random variable,
SRC pp.52-54
- Quick introduction to the
R language.
Discrete-Time Markov Chains
- Main material, PSB Chapters 6 and 12.
- Application: Google PageRank, RecSys, Chapter 12
- R packages: pageRank
Continuous-Time Markov Chains
- Preparation: The exponential distribution family, PSB Chapter 9.
- Main material, PSB Chapter 11.
Hidden Markov Chains
- Preparation:
- Statistical estimation, PSB, Chapter 22.
- Mixture distributions, PSB Chapter 24.
- Smoothing and the bias/variance tradeoff, PSB Chapter 25.
- Main material: TBA, mostly research papers.
- R packages: HMM
- Applications: NLP, time series, biosequences, etc.
Queuing Models
- Preparation:
Transform methods, PSB Chapter 18
- Main material: PSB, Chapter 13
- Applications: Hospital management, communications networks, etc.
- R packages: queueing, simmer
Hazard Functions and Renewal Theory
- Main material: PSB, Chapters 14, 15
- R packages: chosen from CRAN Task View on Survival Analysis
- Application: Modeling Web acccess analysis, e.g.
my paper
- Application: Modeling lost pay in job discrimination litigation,
article
by Pan and Gastwirth
Other Topics as Time Permits