Syllabus (original) (raw)

The following is a tentative schedule for a course on learning dynamical systems offered at Brown University in the Fall of 1995.

Tuesday, September 5

Topic: Organization

Reading: [Kelly, 1994]

Thursday, September 7

Topic: Introduction

Reading: Chapter 4 from [Casti, 1990]

Exercise: LogisticFunction.m

Tuesday, September 12

Topic: Dynamical Systems

Reading: Chapter 1 and 2 from [Dean & Wellman, 1991]

Exercise: LorenzEquations.m

Thursday, September 14

Topic: Graphical Models

Reading: Chapter 8 from [Dean, Allen & Aloimonos, 1995]

Exercise: CellularAutomata.m

Tuesday, September 19

Topic: Bayesian Networks and Markov Processes

Reading: Sections 1 through 5 from ``Decision-Theoretic Planning and Markov Decision Processes''

Exercise: BayesianNetworks.m

Thursday, September 21

Topic: Statistical Inference

Reading: [DeGroot, 1986]

Exercise:

Tuesday, September 26

Topic: Prediction and Explanation

Reading: Introductory chapter from [Weigend & Gershenfeld, 1994]

Reading: Chapters 1 and 2 from [Chatfield, 1989]

Exercise: TimeSeries.m

Thursday, September 28

Topic: Singular Value Decomposition

Reading: ``Singular Value Decomposition - A Primer''

Exercise: SingularValueDecomposition.m

Tuesday, October 3 (Yom Kippur begins at sundown)

Topic: Discrete Fourier Transform

Reading: ``Fourier Transform - A Primer''

Exercise: DiscreteFourierTransform.m

Thursday, October 5

Topic: Delay Coordinate Embedding

Reading: [Sauer, 1994]

Exercise: DelayCoordinateEmbedding.m

Tuesday, October 10

Topic: Learning Bayesian Networks

Reading: [Cooper & Herskovitz, 1992]

Exercise: CooperandHerskovits.m

Thursday, October 12 (Columbus Day)

Topic: Minimum Description Length Methods

Reading: [Lam & Bacchus, 1994]

Exercise:

Tuesday, October 17

Topic: Learning with Graphical Models

Reading: [Buntine, 1994]

Exercise:

Thursday, October 19

Topic: Dirichlet Priors

Reading: [Heckerman, 1995]

Exercise:

Tuesday, October 24

Topic: Coping with Missing Data

Reading: [Russell et al., 1995]

Exercise:

Thursday, October 26

Topic: Gibbs Sampling

Reading: [Geman & Geman, 1984]

Exercise: GibbsSampling.m

Tuesday, October 31 (Halloween)

Topic: Expectation Maximization

Reading: [Dempster et al., 1977]

Thursday, November 2

Topic: Finite Automata

Reading: [Moore, 1956]

Exercise:

Tuesday, November 7 (Election Day)

Topic: Hidden Markov Models

Reading: [Rabiner & Juang, 1986]

Exercise:

Thursday, November 9

Topic: Hidden Markov Models

Reading: [Fraser & Dimitriadis, 1994]

Exercise: BaumWelsh.m

Tuesday, November 14

Topic: Machine Reconstruction

Reading: [Crutchfield & Young, 1990]

Exercise: MachineReconstruction.m

Thursday, November 16

Topic:

Reading:

Exercise:

Tuesday, November 21

Topic: Learning Finite Automata

Reading: [Basye, Dean & Kaelbling, 1995]

Exercise:

Thursday, November 23 (Thanksgiving)

Topic: No class.

Tuesday, November 28

Topic: Project proposals are due.

Reading:

Exercise:

Thursday, November 30

Topic: Diversity Based Methods for Learning Finite Automata

Reading: [Rivest & Schapire, 1987]

Exercise:

Tuesday, December 5

Topic: Probabilistic Finite Automata

Reading: [Ron et al., 1994]

Exercise:

Thursday, December 7

Topic: Neural Networks

Reading:

Exercise:

Tuesday, December 12

Topic: Recurrent Networks

Reading: [Fahlman, 1991]

Exercise: RecurrentNetworks.m

Thursday, December 14

Topic: Learning Finite Automata with Neural Networks

Reading: [Giles et al.]

Exercise:

Tuesday, December 19

Topic: Final projects are due. No class.

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