mraginsky + computer-science   35

[1101.0833] Dynamical systems, simulation, abstract computation
""We survey an area of recent development, relating dynamics to theoretical computer science. We discuss the theoretical limits of simulation and computation of interesting quantities in dynamical systems. We will focus on central objects of the theory of dynamics, as invariant measures and invariant sets, showing that even if they can be computed with arbitrary precision in many interesting cases, there exists some cases in which they can not. We also explain how it is possible to compute the speed of convergence of ergodic averages (when the system is known exactly) and how this entails the computation of arbitrarily good approximations of points of the space having typical statistical behaviour (a sort of constructive version of the pointwise ergodic theorem).""
papers  to-read  ergodic-theory  dynamical-systems  complexity  computer-science  algorithms  simulation 
january 2011 by mraginsky
Subexponential Lower Bound for Randomized Pivot Rules! | Combinatorics and more
"Oliver Friedman, Thomas Dueholm Hansen, and Uri Zwick have managed to prove subexponential lower bounds of the form for ... two basic randomized pivot rules for the simplex algorithm! This is the first result of its kind and deciding if this is possible was an open problem for several decades." And they do it using MDPs!
papers  to-read  computer-science  computation  optimization  linear-programming  dynamic-programming  Markov-decision-processes  lower-bounds 
november 2010 by mraginsky
The Church-Turing Thesis: Breaking the Myth | Lambda the Ultimate
"This paper seeks to explode the myth that Turing Machines (TM) are the universal model for all computation."
papers  blogs  to-read  complexity  computer-science  interesting 
july 2009 by mraginsky
Moser’s Method of Bounding a Program Loop « Gödel’s Lost Letter and P=NP
"The main point is this: an information theory bound yields an upper bound on the running time of a computational process."
information-theory  computer-science  complexity  interesting 
june 2009 by mraginsky
Machine Learning (Theory) » Computability in Artificial Intelligence
"Let me show by analogy why limiting research to computational questions is bad for any field. Except in computer science, computational aspects play little role in the development of fundamental theories: Consider e.g. set theory with axiom of choice, foundations of logic, exact/full minimax for zero-sum games, quantum (field) theory, string theory, … Indeed, at least in physics, every new fundamental theory seems to be less computable than previous ones."
blogs  have-read  science  complexity  computer-science  computation  philosophy  epistemology  AI  learning-theory 
may 2009 by mraginsky
Tutorial schedule
FOCS 2008 tutorials (Terry Tao on randomness in combinatorics; Dan Boneh on crypto; Dan Spielman on graph spectra)
lecture-notes  crypto  computer-science  mathematics 
november 2007 by mraginsky

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