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We are interested in '''Max-Cut''' in the streaming model, and specifically in the tradeoff between approximation and space (storage) complexity.  
 
We are interested in '''Max-Cut''' in the streaming model, and specifically in the tradeoff between approximation and space (storage) complexity.  
 
Formally, in the '''Max-Cut''' problem, the input is a graph $G$, and the goal is to compute the maximum number of edges that cross any single cut $(V_1,V_2)$. This is clearly equivalent to computing the least number of edges that need to be removed to make the graph bipartite.
 
Formally, in the '''Max-Cut''' problem, the input is a graph $G$, and the goal is to compute the maximum number of edges that cross any single cut $(V_1,V_2)$. This is clearly equivalent to computing the least number of edges that need to be removed to make the graph bipartite.
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In the streaming model, we assume that the input graph is seen as a sequence of edges, in an arbitrary order, and the goal is to compute the '''Max-Cut''' value, i.e., the number of edges (or approximate it). There is no need to report the cut itself. For instance, it is easy to approximate '''Max-Cut''' within factor $1/2$ using $O(\log n)$ space, by simply counting the total number edges in the input and reporting $|E(G)|/2$.  
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In the streaming model, we assume that the input graph is seen as a sequence of edges, in an arbitrary order, and the goal is to compute the '''Max-Cut''' value, i.e., the number of edges (or approximate it). There is no need to report the cut itself. For instance, it is easy to approximate Max-Cut within factor $1/2$ using $O(\log n)$ space, by simply counting the total number edges in the input and reporting $|E(G)|/2$.  
  
 
Here is a concrete suggestion for a hard input distribution, which is known to be a hard instance for bipartiteness testing in sparse graphs {{cite|GoldreichR-02}}.  
 
Here is a concrete suggestion for a hard input distribution, which is known to be a hard instance for bipartiteness testing in sparse graphs {{cite|GoldreichR-02}}.  

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