| Date
| Topic
|
| Mon Jan 3
| Introduction to online learning
|
| Wed Jan 5
| The Hedge Algorithm
| Homework1
|
| Mon Jan 10
| Lossless compression using Arithmetic coding
|
| Wed Jan 12
| Universal source coding and the Online Bayes algorithm
| Homework2
|
| Mon Jan 17
| Martin Luther King Day
|
| Wed Jan 19
| Follow the perturbed leader, internal regret, calibration
| Chapter 4, Efficient algorithms for online decision problems Kalai and Vempala
|
|
|
| Homework3
|
| Mon Jan 24
| Variable length Markov models, the Context Algorithm
| Section 5.3
|
| Wed Jan 26
| Equilibria in games: Min-Max, Nash, Correlated equilibrium. Chapter 7 in CBL book.
| Multiagent Systems Yoav Shoham, Kevin Leyton-Brown, Chapter 3.
|
|
|
| Homework4
|
| Mon Jan 31
| Learning in repeated games.
| Chapter 7
|
| Wed Feb 2
| Boosting as a repeated game, Uniform bounds for finite classes.
|
| Mon Feb 7
| VC Theory, Glivenco-Cantelli.
| Chapter 2 in the boosting book, chapters 12, 13 in the Book 3.
|
| Homework5
|
| Wed Feb 9
| Adaboost, Alternating decision trees.
| Some Slides
|
| Mon Feb 14
| No class
|
| Wed Feb 16
| Boosting the Margin
|
| Mon Feb 21 (Fillin class)
| Support vector machines
| A tuturial on support vector machines for pattern recognition Chris Burges.
|
| Wed Feb 23
| Large margin Classification using The Perceptron algorithm
| Large margin classification using the perceptron algorithm Freund and Schapire.
|
| Mon Feb 28
| The generalization ability of online algorithms Cesa-Bianchi, Conconi and Gentile
| Homework6
|
| Mon March 2
| Universal portfolios / Online learning in finance.
| Chapter 10 in Cesa-Bianchi and Lugosi
|
| Wed March 7
| Bootstrap, Bagging and Random Forests
| Random Forests Leo Breiman
|
| Wed March 9
| Final Exam
|
