17,554 research outputs found
Structure theory for the realization of finite state automata Progress report, 1 Nov. 1966 - 30 Apr. 1967
Structure theory for realization of finite state automat
HYPA: Efficient Detection of Path Anomalies in Time Series Data on Networks
The unsupervised detection of anomalies in time series data has important
applications in user behavioral modeling, fraud detection, and cybersecurity.
Anomaly detection has, in fact, been extensively studied in categorical
sequences. However, we often have access to time series data that represent
paths through networks. Examples include transaction sequences in financial
networks, click streams of users in networks of cross-referenced documents, or
travel itineraries in transportation networks. To reliably detect anomalies, we
must account for the fact that such data contain a large number of independent
observations of paths constrained by a graph topology. Moreover, the
heterogeneity of real systems rules out frequency-based anomaly detection
techniques, which do not account for highly skewed edge and degree statistics.
To address this problem, we introduce HYPA, a novel framework for the
unsupervised detection of anomalies in large corpora of variable-length
temporal paths in a graph. HYPA provides an efficient analytical method to
detect paths with anomalous frequencies that result from nodes being traversed
in unexpected chronological order.Comment: 11 pages with 8 figures and supplementary material. To appear at SIAM
Data Mining (SDM 2020
High-resolution truncated plurigaussian simulations for the characterization of heterogeneous formations
Integrating geological concepts, such as relative positions and proportions
of the different lithofacies, is of highest importance in order to render
realistic geological patterns. The truncated plurigaussian simulation method
provides a way of using both local and conceptual geological information to
infer the distributions of the facies and then those of hydraulic parameters.
The method (Le Loc'h and Galli 1994) is based on the idea of truncating at
least two underlying multi-Gaussian simulations in order to create maps of
categorical variable. In this manuscript we show how this technique can be used
to assess contaminant migration in highly heterogeneous media. We illustrate
its application on the biggest contaminated site of Switzerland. It consists of
a contaminant plume located in the lower fresh water Molasse on the western
Swiss Plateau. The highly heterogeneous character of this formation calls for
efficient stochastic methods in order to characterize transport processes.Comment: 12 pages, 9 figure
A GPU-based hyperbolic SVD algorithm
A one-sided Jacobi hyperbolic singular value decomposition (HSVD) algorithm,
using a massively parallel graphics processing unit (GPU), is developed. The
algorithm also serves as the final stage of solving a symmetric indefinite
eigenvalue problem. Numerical testing demonstrates the gains in speed and
accuracy over sequential and MPI-parallelized variants of similar Jacobi-type
HSVD algorithms. Finally, possibilities of hybrid CPU--GPU parallelism are
discussed.Comment: Accepted for publication in BIT Numerical Mathematic
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