View source for CSSS 2008 Beijing-Readings-Week-Three

{{CSSS 2008 Beijing}}
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==Lee Altenberg==

===Lecture Notes===

*[[Media:Altenberg_Lecture_1_4up.pdf | Lecture 1: Introduction to Evolutionary Computation]] (7 MB)

*[http://www.santafe.edu/~altenber/CSSS_BEIJING/2008/Analysis_2008_4up.pdf Lecture 2: Mathematical Analysis of Evolutionary Algorithms] (1 MB)

Pending uploading of my 2008 lecture notes, here are the lectures from the 2007 CSSS Beijing:
*[http://www.santafe.edu/~altenber/CSSS_BEIJING/2007/Lecture_3.4up.pdf Lecture 3: Higher Order Evolutionary Phenomena] (9MB)

===Additional Reading===
*Altenberg, L. , 2004. [http://dynamics.org/Altenberg/PAPERS/OPSAED/ Open Problems in the Spectral Analysis of Evolutionary Dynamics] presents a mathematical framework for evolutionary optimization and some of its unsolved problems.  

*Altenberg, L. , 1994. [http://dynamics.org/Altenberg/PAPERS/STPT/ The Schema Theorem and Price's Theorem] delves into the claims about schema processing as the source of power in genetic algorithms, and recasts the Schema Theorem (Holland 1975) by using Price's Theorem (1970).  It is shown that the Schema Theorem says nothing about a GA's power, but a modification with a different measurement function produces a theorem about evolvability that is a local measure of GA power.  The concept of rugged landscapes is also deconstructed in terms of operator-defined distance.

*Erik van Nimwegen, James P. Crutchfield, and Martijn Huynen. [http://www.santafe.edu/~evca/Papers/nemr.pdf Neutral Evolution of Mutational Robustness.] Proceedings of the National Academy of Science U.S.A. 96:9716-9720 (1999).

*Altenberg, L. , 2004. [http://dynamics.org/Altenberg/PAPERS/MESLLQ/ Modularity in Evolution: Some Low Level Questions] deconstructs the concept of modularity in terms of spaces of variation, and discusses properties needed for modularity to enhance evolvability.

*Erik van Nimwegen and James P. Crutchfield.  [http://www.santafe.edu/~evca/Papers/med.pdf Metastable Evolutionary Dynamics: Crossing Fitness Barriers or Escaping via Neutral Paths?]  Bulletin of Mathematical Biology 62:5:799-848 (Sep 2000)

* Lauren Ancel Meyers, Fredric D. Ancel, Michael Lachmann.  2005.  [http://dx.doi.org/10.1371/journal.pcbi.0010032 Evolution of Genetic Potential].  PLoS Computational Biology  1(3): e32.

* Evolutionary Art at [http://electricsheep.org/ Electric Sheep]


== (Samuel) Qing-Shan Jia==
=== Lecture Notes ===

* [[media:Jia.OO.ppt | Ordinal Optimization: Soft Optimization for Hard Problems]]
* [[media:ResourceNetwork.ppt | How does Spare Capacity and Topology Affect the Security of Resource Networks?]]

=== Additional Reading ===
* [[media: Soft_computing_for_hard_problems.pdf | An Explanation of Ordinal Optimization]].  Ho.  <i>Information Sciences</i>  113,  169-192 (1999).
* [[media: UAP97.pdf | Universal Alignment Probabilities and Subset Selection for Ordinal Optimization]].  Lau and Ho.  <i>Journal of Optimization Theory and Applications</i> 93:3. 455-489 (1997).
* [[media: UBS.pdf | How Topology Affects Security: An Upper Bound of Electric Power Network Security]].  Jia and Zhao.
* [[media: How Much Spare Capacity.pdf | How Much Spare Capacity is Necessary for the Security of Resource Networks?]]  Zhao, Jian and Cao.  <i>Physica A</i> 373, 861-873 (2007).


==Susanne Still==

===Lecture Notes===

July 14. [[Media:Still_CSSS1.pdf | A brief introduction to uses of information theory in machine learning ]]

July 15. [[Media:Still_CSSS2.pdf | Optimal Causal Inference ]]



== Chris Wiggins==
=== Lecture Notes ===

* Bayes
** History
** What he said
** What he didn't say
* Bayes rule in Dynamics
** Random walks
*** Pollen grains
*** Wall street
** Chemical kinetics
** Polymer Physics
* Bayes rule in Statistics
** Why we fit
** Regularization
** Latent variables / Mixture modeling
** Model selection the Bayesian way
** Bayesian density estimation / unsupervised learning
* Alternatives to Bayes
** Cross validation
** pvalueology
** Information theoretic methods

=== Additional Reading ===

* wikipedia (be careful! there's likely to be at least one error per page):
** http://en.wikipedia.org/wiki/Thomas_Bayes
** http://en.wikipedia.org/wiki/Bayes'_theorem
** http://en.wikipedia.org/wiki/Gamma_function
** http://en.wikipedia.org/wiki/Stirling%27s_approximation
** http://en.wikipedia.org/wiki/Method_of_steepest_descent#The_idea_of_Laplace.27s_method
** http://en.wikipedia.org/wiki/Gaussian_integral
* bayes's biography: http://www-gap.dcs.st-and.ac.uk/~history/Mathematicians/Bayes.html
* papers:
** bayes's original essay: http://www.stat.ucla.edu/history/essay.pdf
** mackay's thesis, Chapter 2. (take a look at his book, too below) http://www.inference.phy.cam.ac.uk/mackay/PhD.html
** nice Occam’s razor paper by Zoubin Ghahramani  http://learning.eng.cam.ac.uk/zoubin/papers/05occam/occam.pdf
** schwartz's paper http://www.math.tau.ac.il/~yekutiel/MA%20seminar/Schwarz%201978.pdf
** those of you trained in statistical field theory will like this paper also http://arxiv.org/abs/adap-org/9601001
* mackay's book: http://www.inference.phy.cam.ac.uk/mackay/itila/book.html
* references to books not available online:
** http://research.microsoft.com/~cmbishop/prml/