We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
Elchanan Mossel, Ryan O'Donnell, Rocco A. Servedio
d Abstract] A. C. Gilbert S. Guhay P. Indykz S. Muthukrishnan M. Strauss We give an algorithm for nding a Fourier representation R of B terms for a given discrete signal A of leng...
Anna C. Gilbert, Sudipto Guha, Piotr Indyk, S. Mut...
We study the performance of approximate Nash equilibria for congestion games with polynomial latency functions. We consider how much the price of anarchy worsens and how much the ...
George Christodoulou, Elias Koutsoupias, Paul G. S...
We investigate the problem of computing a minimum set of solutions that approximates within a specified accuracy the Pareto curve of a multiobjective optimization problem. We show...
We study the following problem. Given a weighted planar graph G, assign labels L(v) to vertices so that given L(u), L(v) and L(x) for x ∈ X for any X ⊂ V (G), compute the dist...