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Traversing Probabilistic Graphs
, 1999
"... The problem of traversing probabilistic graphs has been studied for a long time. This is because most of the graphs that we come across, whether it is a network of roads or a set of network links are probabilistic in nature. A probabilistic graph is one where there is a probability associated wit ..."
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Cited by 3 (0 self)
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The problem of traversing probabilistic graphs has been studied for a long time. This is because most of the graphs that we come across, whether it is a network of roads or a set of network links are probabilistic in nature. A probabilistic graph is one where there is a probability associated
Probabilistic Graph and Hypergraph Matching
"... We consider the problem of finding a matching between two sets of features, given complex relations among them, going beyond pairwise. Each feature set is modeled by a hypergraph where the complex relations are represented by hyper-edges. A match between the feature sets is then modeled as a hypergr ..."
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Cited by 67 (0 self)
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hypergraph matching problem. We derive the hyper-graph matching problem in a probabilistic setting represented by a convex optimization. First, we formalize a soft matching criterion that emerges from a probabilistic interpretation of the problem input and output, as opposed to previous methods that treat
CONNECTIVITY IN PROBABILISTIC GRAPHS
, 1959
"... ments for the degree of Doctor of Science. A probabilistic graph is a linear graph in which both nodes and links are subject to random erasure. Such a graph may be thought of as an idealized model of a communi-cation network in which switching centers (nodes) and information channels (links) either ..."
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ments for the degree of Doctor of Science. A probabilistic graph is a linear graph in which both nodes and links are subject to random erasure. Such a graph may be thought of as an idealized model of a communi-cation network in which switching centers (nodes) and information channels (links) either
Probabilistic Graph-Clear
- In Proceedings of the IEEE International Conference on Robotics and Automation
, 2009
"... Abstract — This paper introduces a probabilistic model for multirobot surveillance applications with limited range and possibly faulty sensors. Sensors are described with a footprint and a false negative probability, i.e. the probability of failing to report a target within their sensing range. The ..."
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Cited by 6 (3 self)
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. The model implements a probabilistic extension to our formerly developed deterministic approach for modeling surveillance tasks in large environments with large robot teams known as Graph-Clear. This extension leads to a new algorithm that allows to answer new design and performance questions, namely 1) how
1 Clustering Large Probabilistic Graphs
"... Abstract—We study the problem of clustering probabilistic graphs. Similar to the problem of clustering standard graphs, probabilistic graph clustering has numerous applications, such as finding complexes in probabilistic protein-protein interaction networks and discovering groups of users in affilia ..."
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Cited by 6 (0 self)
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Abstract—We study the problem of clustering probabilistic graphs. Similar to the problem of clustering standard graphs, probabilistic graph clustering has numerous applications, such as finding complexes in probabilistic protein-protein interaction networks and discovering groups of users
Nearest-neighbor Queries in Probabilistic Graphs
"... Abstract — Large probabilistic graphs arise in various domains spanning from social networks to biological and communication networks. An important query in these graphs is the k nearestneighbor query, which involves finding and reporting the k closest nodes to a specific node. This query assumes th ..."
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Cited by 1 (0 self)
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Abstract — Large probabilistic graphs arise in various domains spanning from social networks to biological and communication networks. An important query in these graphs is the k nearestneighbor query, which involves finding and reporting the k closest nodes to a specific node. This query assumes
Probabilistic Pattern Queries over Complex Probabilistic Graphs
"... This paper introduces probabilistic pattern queries over complex probabilistic graphs, a theoretical graph model proposed by us recently for dealing with complex probabilistic graph data of modern applications characterized by uncertainty and imprecision. Effective algorithms implementing such queri ..."
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This paper introduces probabilistic pattern queries over complex probabilistic graphs, a theoretical graph model proposed by us recently for dealing with complex probabilistic graph data of modern applications characterized by uncertainty and imprecision. Effective algorithms implementing
Finding representative nodes in probabilistic graphs
"... We introduce the problem of identifying representative nodes in probabilistic graphs, motivated by the need to produce different simple views to large networks. We define a probabilistic similarity measure for nodes, and then apply clustering methods to find groups of nodes. Finally, a representativ ..."
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Cited by 2 (2 self)
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We introduce the problem of identifying representative nodes in probabilistic graphs, motivated by the need to produce different simple views to large networks. We define a probabilistic similarity measure for nodes, and then apply clustering methods to find groups of nodes. Finally, a
Probabilistic Graph Models for Debugging Software
"... Of all software development activities, debugging—locating the defective source code statements that cause a failure—can be by far the most time-consuming. We employ probabilistic modeling to support programmers in finding defective code. Most defects are identifiable in control flow graphs of softw ..."
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Of all software development activities, debugging—locating the defective source code statements that cause a failure—can be by far the most time-consuming. We employ probabilistic modeling to support programmers in finding defective code. Most defects are identifiable in control flow graphs
Learning in Probabilistic Graphs exploiting Language-Constrained Patterns
"... Abstract. The probabilistic graphs framework models the uncertainty inherent in real-world domains by means of probabilistic edges whose value quantifies the likelihood of the edge existence or the strength of the link it represents. The goal of this paper is to provide a learning method to compute ..."
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Abstract. The probabilistic graphs framework models the uncertainty inherent in real-world domains by means of probabilistic edges whose value quantifies the likelihood of the edge existence or the strength of the link it represents. The goal of this paper is to provide a learning method to compute
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2,355
