25 random regular graphs are generated at each r, |V| level using NetworkX, and algorithms were timed out at 15 minutes. Timed out values were dropped from the data, resulting in less than 25 Samples for some parameter values.</p
Given a graph with non-negative edge weights, the MAXCUT problem is to partition the set of vertice...
We study the boundary of tractability for the max-cut problem in graphs. Our main result shows that ...
We use random sampling as a tool for solving undirected graph problems. We show that the sparse grap...
LG, Stoch, and LIQUi|> denote linegraph-based tensor contraction, stochastic tensor contraction, and...
LG and Stoch denote linegraph-based tensor contraction and stochastic tensor contraction respectivel...
This paper is devoted to the distributed complexity of finding an approximation of the maximum cut i...
We study exact algorithms for the MAX-CUT problem. Introducing a new technique, we present an algori...
This paper is devoted to the distributed complexity of finding an approximation of the maximum cut (...
We initiate the study of hedge connectivity of undirected graphs, motivated by dependent edge failur...
We show that testing reachability in a planar DAG can be performed in parallel in O(log n log n) ...
Max-Cut (or, equivalently, Quadratic Unconstrained Binary Optimization (QUBO)) is one of the most r...
We describe a new exact algorithm for MaxClique, called LMC (short for Large MaxClique), that is esp...
Abstract. Karger (SIAM Journal on Computing, 1999) developed the first fully-polynomial approximatio...
We improve on random sampling techniques for approximately solving problems that involve cuts in gra...
Abstract. The Bipartite Contraction problem is to decide, given a graph G and a parameter k, whether...
Given a graph with non-negative edge weights, the MAXCUT problem is to partition the set of vertice...
We study the boundary of tractability for the max-cut problem in graphs. Our main result shows that ...
We use random sampling as a tool for solving undirected graph problems. We show that the sparse grap...
LG, Stoch, and LIQUi|> denote linegraph-based tensor contraction, stochastic tensor contraction, and...
LG and Stoch denote linegraph-based tensor contraction and stochastic tensor contraction respectivel...
This paper is devoted to the distributed complexity of finding an approximation of the maximum cut i...
We study exact algorithms for the MAX-CUT problem. Introducing a new technique, we present an algori...
This paper is devoted to the distributed complexity of finding an approximation of the maximum cut (...
We initiate the study of hedge connectivity of undirected graphs, motivated by dependent edge failur...
We show that testing reachability in a planar DAG can be performed in parallel in O(log n log n) ...
Max-Cut (or, equivalently, Quadratic Unconstrained Binary Optimization (QUBO)) is one of the most r...
We describe a new exact algorithm for MaxClique, called LMC (short for Large MaxClique), that is esp...
Abstract. Karger (SIAM Journal on Computing, 1999) developed the first fully-polynomial approximatio...
We improve on random sampling techniques for approximately solving problems that involve cuts in gra...
Abstract. The Bipartite Contraction problem is to decide, given a graph G and a parameter k, whether...
Given a graph with non-negative edge weights, the MAXCUT problem is to partition the set of vertice...
We study the boundary of tractability for the max-cut problem in graphs. Our main result shows that ...
We use random sampling as a tool for solving undirected graph problems. We show that the sparse grap...