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cs677:schedule [2014/12/05 00:16] (current)
ryancha created
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 +<!--= I AM ACTIVELY EDITING THIS, EXPECT FREQUENT CHANGES FOR THE REST OF TODAY=-->​
  
 += 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.
 +<!-- PLACE HOLDER: [[Pruning Lab]],,, [[Foundations Homework]],​[[MOM and MLE]],​[[Poisson]],​[[Estimators HW]]
 +there are many useful Tutorials on the web, including [http://​en.wikipedia.org/​wiki/​Particle_filter this one at wikipedia]-->​
 +<table border=1>​
 +<tr>
 +<​th>​Date</​th><​th>​Topic</​th><​th>​Reading</​th><​th>​Homework,​ Labs and Exams</​th>​
 +
 +<tr>
 +<​th>​4-26</​th>​
 +<​td>​[[Subjective Probability]]</​td>​
 +<!-- Syllabus, Frequentist interpretation,​ Random Variable, Joint, Marginal, Conditional-->​
 +<​td>​[[Syllabus]],​ Chapter 1</​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​4-27</​th>​
 +<​td>​RV'​s,​ Independence,​ Bayes law</​td>​
 +<!-- Joint, Marginal, Conditional-->​
 +<​td>​Chapter 2</​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​4-29</​th>​
 +<​td></​td>​
 +<​td></​td>​
 +<​td>​[[Probability Homework]]</​td>​
 +
 +<​tr><​tr>​
 +
 +<tr>
 +<​th>​5-2</​th>​
 +<​td>​More distributions,​ Continuous RV's, Bayes with Continuous RV's (normal-normal)</​td>​
 +<​td>​Sections 3.1-3.7</​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​5-3</​th>​
 +<​td>​Bayes (Normal-Normal,​ Normal-Gamma)</​td>​
 +<​td>​Sections 3.8, 4.1-4.7, 5.1-5.9 (Familiarize your self with these distributions),​ 8.6</​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​5-4</​th>​
 +<​td>​Functions of random variables (Normal-IGamma),​ Conjugacy</​td>​
 +<​td></​td>​
 +<​td>​[[RVs and Distributions HW]]</​td>​
 +
 +<tr>
 +<​th>​5-6</​th>​
 +<​td></​td>​
 +<​td></​td>​
 +<​td></​td>​
 +
 +<​tr><​tr>​
 +
 +<tr>
 +<​th>​5-9</​th>​
 +<​td>​Beta-Binomial,​ Expectations</​td>​
 +<​td>​Sections 6.1-6.4, 7.1-7.3</​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​5-10</​th>​
 +<​td>​Estimators,​ Graphical models, Discrete and continuous, Inference in the Discrete Case</​td>​
 +<​td>​Sections 7.5-7.7</​td>​
 +<​td>​[[Conjugate Pair, and Functions of Random Variables]]</​td>​
 +
 +<tr>
 +<​th>​5-11</​th>​
 +<​td>​Catch up</​td>​
 +<​td></​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​5-13</​th>​
 +<​td></​td>​
 +<​td></​td>​
 +<​td>​[[Sampling,​ Estimators and GM'​s]]</​td>​
 +
 +<​tr><​tr>​
 +
 +<tr>
 +<​th>​5-16</​th>​
 +<​td>​Temporal Models: Stochastic Processes, Markov Chains, Hidden Markov Models, Kalman filter</​td>​
 +<​td>​Section 3.10</​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​5-17</​th>​
 +<​td>​Sampling,​ Approximate Inference, Rejection, Likelihood Weighting, Particle Filter, [[Sampling Sample Code]]</​td>​
 +<​td>​Sections 12.1-12.4</​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​5-18</​th>​
 +<​td>​MCMC:​ Gibbs Sampling, Metropolis, [[Sampling Sample Code]]</​td>​
 +<​td>​Section 12.5</​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​5-20</​th>​
 +<​td></​td>​
 +<​td></​td>​
 +<​td>​[[Filters Lab]]</​td>​
 +
 +<​tr><​tr>​
 +
 +<tr>
 +<​th>​5-23</​th>​
 +<​td>​Metropolis Proof, Parameter Learning</​td>​
 +<​td></​td>​
 +<​td>​[[Gibbs Homework]]</​td>​
 +
 +<tr>
 +<​th>​5-24</​th>​
 +<​td>​Structure Learning</​td>​
 +<​td></​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​5-25</​th>​
 +<​td>​Utility and Decisions</​td>​
 +<​td>​Section 6.1, Chapter 15, and </td>
 +<​td></​td>​
 +
 +<tr>
 +<​th>​5-27</​th>​
 +<​td></​td>​
 +<​td></​td>​
 +<​td></​td>​
 +
 +<​tr><​tr>​
 +
 +<tr>
 +<​th>​5-30</​th>​
 +<​td>​Holiday,​ no class</​td>​
 +<​td></​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​5-31</​th>​
 +<​td>​Value of Information</​td>​
 +<​td>​[http://​aml.cs.byu.edu/​~kseppi/​cs470sp10files/​evsi_v4.pdf EVSI]</​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​6-1</​th>​
 +<​td>​infinite models if time permits</​td>​
 +<​td></​td>​
 +<​td>'''​Individual'''​ [[MCMC Lab]]-- This is not a group project. See the [[Syllabus]] for more info.</​td>​
 +
 +<tr>
 +<​th>​6-3</​th>​
 +<​td></​td>​
 +<​td></​td>​
 +<​td></​td>​
 +
 +<​tr><​tr>​
 +
 +<tr>
 +<​th>​6-6</​th>​
 +<​td>​Graphical models part two, d-separability,​ pruning</​td>​
 +<​td>​[[Pruning and d-separability]]</​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​6-7</​th>​
 +<​td>​No class, use this time for labs</​td>​
 +<​td></​td>​
 +<​td>​[[Learning Lab]]</​td>​
 +
 +<tr>
 +<​th>​6-8</​th>​
 +<​td>​[[Continuous EVSI]]</​td>​
 +<​td></​td>​
 +<​td></​td>​
 +
 +<tr>
 +<​th>​6-10</​th>​
 +<​td></​td>​
 +<​td></​td>​
 +<​td></​td>​
 +
 +<​tr><​tr>​
 +
 +<tr>
 +<​th>​6-13</​th>​
 +<​td>​Open Discussion of the labs and Final</​td>​
 +<​td></​td>​
 +<​td>​[[Pruning Lab]] Note also that I can not accept anything except the Final after this.</​td>​
 +
 +<tr>
 +<​th>​6-16</​th>​
 +<​td>​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.</​td>​
 +<​td></​td>​
 +<​td></​td>​
 +
 +</​table>​
 +
 +[[Helpful Links]]
cs677/schedule.txt ยท Last modified: 2014/12/05 00:16 by ryancha
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