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Distributed Computation of Sparse Cuts
, 2013
"... Finding sparse cuts is an important tool in analyzing largescale distributed networks such as the Internet and PeertoPeer networks, as well as largescale graphs such as the web graph, online social communities, and VLSI circuits. Sparse cuts are useful in graph clustering and partitioning among ..."
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Finding sparse cuts is an important tool in analyzing largescale distributed networks such as the Internet and PeertoPeer networks, as well as largescale graphs such as the web graph, online social communities, and VLSI circuits. Sparse cuts are useful in graph clustering and partitioning among
How good are sparse cuttingplanes
 In Integer Programming and Combinatorial Optimization
, 2014
"... Abstract. Sparse cuttingplanes are often the ones used in mixedinteger programing (MIP) solvers, since they help in solving the linear programs encountered during branch&bound more efficiently. However, how well can we approximate the integer hull by just using sparse cuttingplanes? In ord ..."
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Abstract. Sparse cuttingplanes are often the ones used in mixedinteger programing (MIP) solvers, since they help in solving the linear programs encountered during branch&bound more efficiently. However, how well can we approximate the integer hull by just using sparse cutting
Sparse Cut Projections in Graph Streams
"... Finding sparse cuts is an important tool for analyzing large graphs that arise in practice, such as the web graph, online social communities, and VLSI circuits. When dealing with such graphs having billions of nodes, it is often hard to visualize global partitions. While studies on sparse cuts have ..."
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Finding sparse cuts is an important tool for analyzing large graphs that arise in practice, such as the web graph, online social communities, and VLSI circuits. When dealing with such graphs having billions of nodes, it is often hard to visualize global partitions. While studies on sparse cuts
Finding sparse cuts locally using evolving sets
 In STOC'09: Proceedings of the 41st Annual ACM symposium on Theory of Computing
, 2009
"... A local graph partitioning algorithm finds a set of vertices with small conductance (i.e. a sparse cut) by adaptively exploring part of a large graph G, starting from a specified vertex. For the algorithm to be local, its complexity must be bounded in terms of the size of the set that it outputs, wi ..."
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Cited by 41 (0 self)
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A local graph partitioning algorithm finds a set of vertices with small conductance (i.e. a sparse cut) by adaptively exploring part of a large graph G, starting from a specified vertex. For the algorithm to be local, its complexity must be bounded in terms of the size of the set that it outputs
Distributed Averaging in the presence of a Sparse Cut
 Principles of Distributed Computing (PODC
"... We consider the question of averaging on a graph that has one sparse cut separating two subgraphs that are internally well connected. While there has been a large body of work devoted to algorithms for distributed averaging, nearly all algorithms involve only convex updates. In this paper, we sugges ..."
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We consider the question of averaging on a graph that has one sparse cut separating two subgraphs that are internally well connected. While there has been a large body of work devoted to algorithms for distributed averaging, nearly all algorithms involve only convex updates. In this paper, we
Finding Small Sparse Cuts by Random Walk
"... Abstract. We study the problem of finding a small sparse cut in an undirected graph. Given an undirected graph G = (V,E) and a parameter k ≤ E, the small sparsest cut problem is to find a set S ⊆ V with minimum conductance among all sets with volume at most k. Using ideas developed in local graph ..."
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Abstract. We study the problem of finding a small sparse cut in an undirected graph. Given an undirected graph G = (V,E) and a parameter k ≤ E, the small sparsest cut problem is to find a set S ⊆ V with minimum conductance among all sets with volume at most k. Using ideas developed in local graph
Sparse cuts, matchingcuts and leafy trees in graphs
, 2006
"... The graph shown on the cover of this thesis is one of the graphs used in the N Pcompleteness proofs of Chapter 3. The bold edges indicate a matchingcut in this graph, consisting of two of the six minimal matchingcuts possible in this graph. The cut consisting of the eleven dashed edges separates ..."
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Cited by 9 (2 self)
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The graph shown on the cover of this thesis is one of the graphs used in the N Pcompleteness proofs of Chapter 3. The bold edges indicate a matchingcut in this graph, consisting of two of the six minimal matchingcuts possible in this graph. The cut consisting of the eleven dashed edges separates
Many Sparse Cuts via Higher Eigenvalues
"... Cheeger’s fundamental inequality states that any edgeweighted graph has a vertex subset S such that its expansion (a.k.a. conductance) is bounded as follows: φ(S) def w(S, S̄) min{w(S), w(S̄)} 6 2 λ2, where w is the total edge weight of a subset or a cut and λ2 is the second smallest eigenvalue of ..."
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of the total weight and φ(S) 6 C λk log k. Both results are the best possible up to constant factors. The underlying algorithmic problem, namely finding k subsets such that the maximum expansion is minimized, besides extending sparse cuts to more than one subset, appears to be a natural clustering problem
Sybil Detection via Distributed Sparse Cut Monitoring
"... Abstract—Decentralized reputation systems help to enforce discipline and fairness in large unstructured and adhoc systems by rewarding good behavior and penalizing dishonest or greedy behavior. They are essential in large networks of independent nodes where centralized monitoring of node behavior i ..."
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Abstract—Decentralized reputation systems help to enforce discipline and fairness in large unstructured and adhoc systems by rewarding good behavior and penalizing dishonest or greedy behavior. They are essential in large networks of independent nodes where centralized monitoring of node behavior is difficult due to the sheer size of the network. Sybil nodes pose a threat to the reputation systems by false referrals through sybil identities. We propose a scalable and distributed algorithm to identify attack edges and quarantine sybil clusters. This algorithm works well with dynamic trust graphs as nodes do not need to store any precomputed data. Index Terms—sybils, reputation, peer to peer, social networks I.
Results 1  10
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