Lecture 1

Probability Refresher

Lecture 3

• Proof of Cesaro Means
• Entropy Rate, from I.J. Taneja, "Generalized Information Measures and Their Applications",   book preprint

Lecture 4

• Dan Klein, "Lagrange Multipliers Without Permanent Scarring"
• Henry C. Edwards, "Ladders, Moats, and Lagrange Multipliers" 
  

Lecture 5

• Harry Printz, "Tutorial on Arithmetic Coding"
• G.G. Langdon, "Introduction to Arithmetic Coding"
• Howard and Vitter, "Analysis of Arithmetic Coding For Data Compression"
• A list of resources on Arithmetic Coding, look in particular at the "Arithmetic Coding Revealed" tutorial

This is additional material, about actual coding, not covered in class. You are not responsible for it

• Introduction to error correcting codes (from the navy academy?)  - the interesting part is under the "The Hamming metric" subsection
• Error Correcting Codes (from Hong-Kong Polytechnic University)
• Lecture Notes from Victoria University of Wellington Math 314 - Lectures 5 to 9 are interesting, but the entire web site is a useful introduction to coding.
  

Lecture 12

• Adami's paper: "Information Theory in Molecular Biology"
• Toby Berger's Shannon Lecture
• Basic introduction to neuron physiology
• Another basic introduction to neuron physiology

Lecture 13

• Berger and Levenshtein, "Asymptotic Efficiency of Two-Stage Disjunctive Testing", IEEE Trans Info Theory, 48(7):1741-1749, Sept. 2002

MISC

• In class, we talked about "curse of dimensionality". This is a link to: J.H. Friedman, On Bias, Variance, 0/1-loss, and the curse-of-dimensionality