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]
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]
Tuesday, October 17
Topic: Learning with Graphical Models
Reading: [Buntine, 1994]
Thursday, October 19
Topic: Dirichlet Priors
Reading: [Heckerman, 1995]
Tuesday, October 24
Topic: Coping with Missing Data
Reading: [Russell et al., 1995]
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]
Tuesday, November 7 (Election Day)
Topic: Hidden Markov Models
Reading: [Rabiner & Juang, 1986]
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
Tuesday, November 21
Topic: Learning Finite Automata
Reading: [Basye, Dean & Kaelbling, 1995]
Thursday, November 23 (Thanksgiving)
Topic: No class.
Tuesday, November 28
Topic: Project proposals are due.
Thursday, November 30
Topic: Diversity Based Methods for Learning Finite Automata
Reading: [Rivest & Schapire, 1987]
Tuesday, December 5
Topic: Probabilistic Finite Automata
Reading: [Ron et al., 1994]
Thursday, December 7
Topic: Neural Networks
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.]
Tuesday, December 19
Topic: Final projects are due. No class.

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