neal young / Koufogiannakis13Nearly

  • publication/Koufogiannakis13Nearly.png We give an approximation algorithm for packing and covering linear programs (linear programs with non-negative coefficients). Given a constraint matrix with \(N\) non-zeros, \(r\) rows, and \(c\) columns, the algorithm (with high probability) computes feasible primal and dual solutions whose costs are within a factor of \(1+\epsilon\) of the optimal cost in time \(O((r+c)\log(N)/\epsilon^2 + N)\).
    Journal version of [2007].

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