A Faster Algorithm for Linear Programming and the Maximum Flow Problem II
berkeley.edu
A Faster Algorithm for Linear Programming and the Maximum Flow Problem II
In this talk, I will present a new algorithm for solving linear programs. Given a linear program with n variables, m > n constraints, and bit complexity L, our algorithm runs in Õ(sqrt(n) L) iterations each consisting of solving Õ(1) linear systems and additional nearly linear time computation. Our method improves upon the convergence rate of ...
2014年12月4日
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There are many common variations of the maximum flow problem. Here are four of them. (a) There are many sources and many sinks, and we wish to maximize the total flow from all sources to all sinks. (b) Each vertex also has a capacity on the maximum flow that can enter it. (c) Each edge has not only a capacity, but also a lower bound on the flow it must carry. (d) The outgoing flow from each node u is not the same as the incoming flow, but is smaller by a factor of (1-ϵu), where ϵu is a loss coef
There are many common variations of the maximum flow problem. Here are four of them. (a) There are many sources and many sinks, and we wish to maximize the total flow from all sources to all sinks. (b) Each vertex also has a capacity on the maximum flow that can enter it. (c) Each edge has not only a capacity, but also a lower bound on the flow it must carry. (d) The outgoing flow from each node u is not the same as the incoming flow, but is smaller by a factor of (1-ϵu), where ϵu is a loss coef
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