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A linear lower bound on the unbounded error probabilistic communication complexity
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Simulated annealing in convex bodies and an O*(n4) volume algorithm
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On Computation and Communication with Small Bias
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Nash equilibria in random games
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An Approximation Algorithm for Approximation Rank
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SIAM Journal on Computing
Proceedings of the forty-third annual ACM symposium on Theory of computing
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We study the ε-rank of a real matrix A, defined for any ε 0 as the minimum rank over matrices that approximate every entry of A to within an additive ε. This parameter is connected to other notions of approximate rank and is motivated by problems from various topics including communication complexity, combinatorial optimization, game theory, computational geometry and learning theory. Here we give bounds on the ε-rank and use them for algorithmic applications. Our main algorithmic results are (a) polynomial-time additive approximation schemes for Nash equilibria for 2-player games when the payoff matrices are positive semidefinite or have logarithmic rank and (b) an additive PTAS for the densest subgraph problem for similar classes of weighted graphs. We use combinatorial, geometric and spectral techniques; our main new tool is an algorithm for efficiently covering a convex body with translates of another convex body.