Syllabus
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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