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The Steiner kcut problem
, 2006
"... We consider the Steiner kcut problem which generalizes both the kcut problem and the multiway cut problem. The Steiner kcut problem is defined as follows. Given an edgeweighted undirected graph G =(V,E), a subset of vertices X ⊆ V called terminals, and an integer k ≤X, the objective is to find ..."
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Cited by 5 (0 self)
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We consider the Steiner kcut problem which generalizes both the kcut problem and the multiway cut problem. The Steiner kcut problem is defined as follows. Given an edgeweighted undirected graph G =(V,E), a subset of vertices X ⊆ V called terminals, and an integer k ≤X, the objective
Maxcut Problem
, 2007
"... Maxcut problem is one of many NPhard graph theory problems which attracted many researchers over the years. Though there is almost no hope in finding a polynomialtime algorithm for maxcut problem, various heuristics, or combination of optimization and heuristic methods have been developed to solv ..."
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Maxcut problem is one of many NPhard graph theory problems which attracted many researchers over the years. Though there is almost no hope in finding a polynomialtime algorithm for maxcut problem, various heuristics, or combination of optimization and heuristic methods have been developed
The minimum Gc cut problem
"... Abstract. In this paper we study the complexity and approximability of the Gccut problem. Given a complete undirected graph Kn = (V; E) with V  = n, edge weighted by w(vi, vj) ≥ 0 and an undirected cluster graph, Gc = (Vc, Ec), with V c  = k, a kcut is a partition V1,..., Vk of V (G) such t ..."
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Abstract. In this paper we study the complexity and approximability of the Gccut problem. Given a complete undirected graph Kn = (V; E) with V  = n, edge weighted by w(vi, vj) ≥ 0 and an undirected cluster graph, Gc = (Vc, Ec), with V c  = k, a kcut is a partition V1,..., Vk of V (G
An Investigation of the MaxCut Problem
, 2004
"... The MaxCut problem seeks to partition the vertices of a graph into two sets such that the weight of the edges joining those sets is maximized. The MaxCut problem has been of continued research interest and has developed an extensive literature. After reviewing of a small portion of that literature, ..."
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Cited by 1 (0 self)
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The MaxCut problem seeks to partition the vertices of a graph into two sets such that the weight of the edges joining those sets is maximized. The MaxCut problem has been of continued research interest and has developed an extensive literature. After reviewing of a small portion of that literature
On the complexity of the Maximum Cut problem
 Nordic Journal of Computing
, 1991
"... The complexity of the simple maxcut problem is investigated for several special classes of graphs. It is shown that this problem is NPcomplete when restricted to one of the following classes: chordal graphs, undirected path graphs, split graphs, tripartite graphs, and graphs that are the complement ..."
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Cited by 16 (4 self)
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polynomial time algorithms for the simple max cut problem. 1 Introduction One of the best known combinatorial graph problems is the max cut problem. In this problem, we have a weighted, undirected graph G = (V; E) and we look for a partition of the vertices of G into two disjoint sets, such that the total
Approximation Algorithm for the MaxCut Problem
 Combinatorics, Probability and Computing
, 1993
"... In this project, we investigated several approximation algorithms for the MaxCut problem. ..."
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Cited by 5 (0 self)
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In this project, we investigated several approximation algorithms for the MaxCut problem.
Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming
 Journal of the ACM
, 1995
"... We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds the solution ..."
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Cited by 1211 (13 self)
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We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds
"GrabCut”  interactive foreground extraction using iterated graph cuts
 ACM TRANS. GRAPH
, 2004
"... The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g. Magic Wand, or edge (contrast) information, e.g. Intelligent Scissors. Recently ..."
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Cited by 1130 (36 self)
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The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g. Magic Wand, or edge (contrast) information, e.g. Intelligent Scissors
Randomized Heuristics for the MaxCut Problem
 Optimization Methods and Software
, 2002
"... Given an undirected graph with edge weights, the MAXCUT problem consists in finding a partition of the nodes into two subsets, such that the sum of the weights of the edges having endpoints in different subsets is maximized. ..."
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Cited by 41 (16 self)
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Given an undirected graph with edge weights, the MAXCUT problem consists in finding a partition of the nodes into two subsets, such that the sum of the weights of the edges having endpoints in different subsets is maximized.
Fast approximate energy minimization via graph cuts
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2001
"... In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function’s smoothness term must only involve pairs of pixels. We propose two algorithms that use graph cuts to compute a local minimum even when v ..."
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Cited by 2120 (61 self)
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In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function’s smoothness term must only involve pairs of pixels. We propose two algorithms that use graph cuts to compute a local minimum even when
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