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Gpu-accelerated relaxed graph pattern matching algorithms
Graph pattern matching is widely used in real-world applications, such as social network analysis. Since the traditional subgraph isomorphism is...
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Graph Algorithms
We have seen two major classes of algorithms that approach the top-k retrieval problem in their own unique ways. One recursively partitions a vector...
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Searching for Software Vulnerabilities Using an Ensemble of Algorithms for the Analysis of a Graph Representation of the Code
AbstractThis article analyzes the existing methods for searching for software vulnerabilities. For methods using deep learning models on a graph...
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Empirical characterization of graph sampling algorithms
Graph sampling allows mining a small representative subgraph from a big graph. Sampling algorithms deploy different strategies to replicate the...
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Reducing classifier overconfidence against adversaries through graph algorithms
In this work we show that deep learning classifiers tend to become overconfident in their answers under adversarial attacks, even when the classifier...
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Embedding residuals in graph-based solutions: the E-ResSAGE and E-ResGAT algorithms. A case study in intrusion detection
AbstractNeural network architectures have been used to address multiple real-world problems with high success. Their extension to graph-structured...
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Graph-based algorithms for phase-type distributions
Phase-type distributions model the time until absorption in continuous or discrete-time Markov chains on a finite state space. The multivariate...
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Investigation of graph-based clustering approaches along with graph neural networks for modeling armed conflict in Bangladesh
Determining fatality rates—a critical component of conflict analysis and comprehending the dynamics of armed conflict in Bangladesh are the main...
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Knowledge discovery assistants for crash simulations with graph algorithms and energy absorption features
We propose the representation of data from finite element car crash simulations in a graph database to empower analysis approaches. The industrial...
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Graph-based comparative analysis of learning to rank datasets
The relative success of learning to rank algorithms has raised the attention of the research community for develo** efficient and effective ranking...
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An adaptive graph sampling framework for graph analytics
In large-scale data processing, graph analytics of complex interaction networks are indispensable. As the whole graph processing and analytics can be...
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Fast parallel algorithms for finding elementary circuits of a directed graph: a GPU-based approach
Circuits in a graph are interesting structures and identifying them is of an important relevance for many applications. However, enumerating circuits...
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Classification of healthy and epileptic seizure EEG signals based on different visibility graph algorithms and EEG time series
Recently, the idea of processing time series by transforming them onto graphs has been used in many studies. One of the simple methods proposed to...
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Graph analysis using a GPU-based parallel algorithm: quantum clustering
The article introduces a new method for applying Quantum Clustering to graph structures. Quantum Clustering (QC) is a density-based unsupervised...
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Winner Determination Algorithms for Graph Games with Matching Structures
Cram , Domineering , and Arc Kayles are well-studied combinatorial games. They are interpreted as edge-selecting-type games on graphs, and the selected...
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Principal component analysis based on graph embedding
Dimensionality reduction plays an important role in image recognition and data mining. Traditional methods extract features from data itself and...
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Almost-Smooth Histograms and Sliding-Window Graph Algorithms
We study algorithms for the sliding-window model, an important variant of the data-stream model, in which the goal is to compute some function of a...
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A new hybrid strategy in medical image registration based on graph transformation matching and mean-based RANSAC algorithms
Medical image registration is a preprocessing stage in a variety of applications such as change detection and mosaicking. Matching is one of the...
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An analysis of one-to-one matching algorithms for entity resolution
Entity resolution (ER) is the task of finding records that refer to the same real-world entities. A common scenario, which we refer to as Clean-Clean...
