proj-future-mathToLearn

Material already "learned" in class that should be reviewed (this has first priority because the reward per unit time is better since I already half understand this stuff):

NameDescriptionStatusNotes
Vaughn Pratt stuff: algebraic logic i read a little bit on airplanes, etc CS353 handouts chapters 1-3
Vaughn Pratt stuff: category theory Graphs with paths. Also, a very general framework for universal algebra i read a little bit on airplanes, etc CS353 handout, chapter 4
Vaughn Pratt stuff: Chu spaces i don't understand them intuitively yet, but anything Vaugn likes must be cool not started CS353 Chu Space quarter class notes, also http://chu.stanford.edu/guide.html
Chuck's physics bookThe mathematics of modern physics in one concise package on first chapter
Review linear algebra not started
harvard's intro math courses \ http://www.math.harvard.edu/~ctm/home/text/class/harvard/55a/08/html/index.html http://www.math.harvard.edu/~ctm/home/text/class/harvard/55b/09/html/index.html https://www.google.com/search?client=ubuntu&channel=fs&q=harvard+55a+55b&ie=utf-8&oe=utf-8
Review modern algebra not started
(Re)read Endertonin middle of book
Review linear systems theory and intro control theory not started
Review the reader from graduate linear systems class not started
Review statistical signal processing not started
Read Basic Category Theory for Computer Scientists by Pierce not started
Mine that combinatorics paper Learn the details of the stuff in https://www.dpmms.cam.ac.uk/~wtg10/2cultures.pdfread the paper once

New material:

http://www.refsmmat.com/statistics/http://www.itl.nist.gov/div898/handbook/http://www.stat.cmu.edu/~larry/all-of-statistics/http://www.statistics4u.com/fundstat_eng/http://onlinestatbook.com/http://www.uvm.edu/~bbeckage/Teaching/DataAnalysis/AssignedPapers/Cohen_1990.pdfhttp://msemac.redwoods.edu/~darnold/math15/RActivities.php (stuff recc. by https://speakerdeck.com/jakevdp/statistics-for-hackers?slide=127 : Bayesian Methods for Hackers by Cam Davidson-Pillon, Chris Fonnesbeck’s Scipy 2015 talk, Statistical Thinking for Data Science, Statistics Is Easy, a book by Shasha & Wilson)
NameDescriptionStatusNotes
Differential geometry not started Need to learn in order to understand grandfather's thesis!
Algebraic geometry not started
Differential topology not started
Algebraic topology not started
Set theory and transfinite stuff not started
Statistics not started https://pavpanchekha.com/blog/stats1.html http://greenteapress.com/thinkstats2/ http://www3.wabash.edu/econometrics/EconometricsBook/index.htm http://bayes.wustl.edu/etj/prob/book.pdf
Taleb's book on risk Silent Risknot started
Mandelbrot's seven states of randomness have read the wiki page https://en.wikipedia.org/wiki/Seven_states_of_randomness
Grandy's thesis Learn enough math to understand my grandfather's thesis not started "Homothetic Correspondences Between Riemannian Spaces" by E. Baylis Shanks
cohomology Learn about cohomology (and homology and homotopy to boot)not started
homotopy type theory http://homotopytypetheory.org/book/ also stuff hyperlinked at the end of section [1]not started
type theory https://en.wikipedia.org/wiki/Intuitionistic_type_theorynot started
network science, extremal properties of graph metrics http://thesis.library.caltech.edu/6749/1/DionysiosBarmpoutis-PhDThesis.pdfnot started
game theory not started
complex analysis found http://www.math.binghamton.edu/dennis/complex.pdf on sidewalk, probably used at UCSD (also from http://math.sfsu.edu/beck/complex.html )not started
http://betterexplained.com/cheatsheet/not started
the books that chuck recommended
https://www.quantstart.com/articles/How-to-Learn-Advanced-Mathematics-Without-Heading-to-University-Part-3 and https://www.quantstart.com/articles/How-to-Learn-Advanced-Mathematics-Without-Heading-to-University-Part-3 and parts 1 and 2

this website mentions some things that may be of interest: