= A general outline of the class =
This is really more of a list of topics than a schedule. It is subject to frequent change... please check back often as dates are likely to change.
Homework and Labs are due ON THE DATE where the homework or lab is linked.
{| border="1"
!colspan="1"|Date
!colspan="1"|Topic
!colspan="1"|Reading
!colspan="1"|Homework, Labs and Exams
|-
|4-26
|[[Subjective Probability]]
|[[Syllabus]], Chapter 1
|

|-
|4-27
|RV's, Independence, Bayes law
|Chapter 2
|

|-
|4-29
|
|
|[[Probability Homework]]

|-|-

|-
|5-2
|More distributions, Continuous RV's, Bayes with Continuous RV's (normal-normal)
|Sections 3.1-3.7
|

|-
|5-3
|Bayes (Normal-Normal, Normal-Gamma)
|Sections 3.8, 4.1-4.7, 5.1-5.9 (Familiarize your self with these distributions), 8.6
|

|-
|5-4
|Functions of random variables (Normal-IGamma), Conjugacy
|
|[[RVs and Distributions HW]]

|-
|5-6
|
|
|

|-|-

|-
|5-9
|Beta-Binomial, Expectations
|Sections 6.1-6.4, 7.1-7.3
|

|-
|5-10
|Estimators, Graphical models, Discrete and continuous, Inference in the Discrete Case
|Sections 7.5-7.7
|[[Conjugate Pair, and Functions of Random Variables]]

|-
|5-11
|Catch up
|
|

|-
|5-13
|
|
|[[Sampling, Estimators and GM's]]

|-|-

|-
|5-16
|Temporal Models: Stochastic Processes, Markov Chains, Hidden Markov Models, Kalman filter
|Section 3.10
|

|-
|5-17
|Sampling, Approximate Inference, Rejection, Likelihood Weighting, Particle Filter, [[Sampling Sample Code]]
|Sections 12.1-12.4
|

|-
|5-18
|MCMC: Gibbs Sampling, Metropolis, [[Sampling Sample Code]]
|Section 12.5
|

|-
|5-20
|
|
|[[Filters Lab]]

|-|-

|-
|5-23
|Metropolis Proof, Parameter Learning
|
|[[Gibbs Homework]]

|-
|5-24
|Structure Learning
|
|

|-
|5-25
|Utility and Decisions
|Section 6.1, Chapter 15, and 
|

|-
|5-27
|
|
|

|-|-

|-
|5-30
|Holiday, no class
|
|

|-
|5-31
|Value of Information
|[http://aml.cs.byu.edu/~kseppi/cs470sp10files/evsi_v4.pdf EVSI]
|

|-
|6-1
|infinite models if time permits
|
|'''Individual''' [[MCMC Lab]]-- This is not a group project. See the [[Syllabus]] for more info.

|-
|6-3
|
|
|

|-|-

|-
|6-6
|Graphical models part two, d-separability, pruning
|[[Pruning and d-separability]]
|

|-
|6-7
|No class, use this time for labs
|
|[[Learning Lab]]

|-
|6-8
|[[Continuous EVSI]]
|
|

|-
|6-10
|
|
|

|-

|-
|6-13
|Open Discussion of the labs and Final
|
|[[Pruning Lab]] Note also that I can not accept anything except the Final after this.

|-
|6-16
|The Final will be a take home exam. It will be posted here: [[Final]]. Note that it (1) '''must''' be turned in on time, I cannot accept it late and (2) must be done independently not as a group or pair, no discussion of any kind.
|
|

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