We consider a system of linear constraints over any finite abelian group $G$ of the following form: $\\ell_i(x_1,\\ldots,x_n) \\equiv \\ell_{i,1}x_1+\\cdots+\\ell_{i,n}x_n \\in A_i$ for $i=1,\\ldots,t$ and each $A_i \\subset G$,
The study of Gaussian mixture distributions goes back to the late 19th century, when Pearson introduced the method of moments to analyze the statistics of a crab population.
I will talk about a simple and interesting way to link Évariste Galois(1811-1832) and John Nash(1928- ). I will also present some issues that I encountered during my explorations while establishing this link.
Embedded systems are increasingly being deployed in a wide variety of applications. Most, if not all, of these applications involve an electronic controller with discrete behaviour controlling a continuously evolving plant.
Ryan Williams, a postdoc at IBM Almaden, posted a manuscript about a week ago on his home page (http://www.cs.cmu.edu/~ryanw/) proving that bounded depth circuits with AND, OR and MOD-m
Ryan Williams, a postdoc at IBM Almaden, posted a manuscript about a week ago on his home page (http://www.cs.cmu.edu/~ryanw/) proving that bounded depth circuits with AND, OR and MOD-m
In a 2-Prover 1-Round Game, a verifier draws a pair of questions (X,Y ) from a distribution D and sends one each to two co-operating, non-communicating players who need to respond back with answers A,B.
