Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: CADDeLaG: Framework for distributed anomaly detection in large dense
  graph sequences   Random walk based distance measures for graphs such as commute-time distance
are useful in a variety of graph algorithms, such as clustering, anomaly
detection, and creating low dimensional embeddings. Since such measures hinge
on the spectral decomposition of the graph, the computation becomes a
bottleneck for large graphs and do not scale easily to graphs that cannot be
loaded in memory. Most existing graph mining libraries for large graphs either
resort to sampling or exploit the sparsity structure of such graphs for
spectral analysis. However, such methods do not work for dense graphs
constructed for studying pairwise relationships among entities in a data set.
Examples of such studies include analyzing pairwise locations in gridded
climate data for discovering long distance climate phenomena. These graphs
representations are fully connected by construction and cannot be sparsified
without loss of meaningful information. In this paper we describe CADDeLaG, a
framework for scalable computation of commute-time distance based anomaly
detection in large dense graphs without the need to load the entire graph in
memory. The framework relies on Apache Spark's memory-centric cluster-computing
infrastructure and consists of two building blocks: a decomposable algorithm
for commute time distance computation and a distributed linear system solver.
We illustrate the scalability of CADDeLaG and its dependency on various factors
using both synthetic and real world data sets. We demonstrate the usefulness of
CADDeLaG in identifying anomalies in a climate graph sequence, that have been
historically missed due to ad hoc graph sparsification and on an election
donation data set.

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The categories of this paper are: chem-ph
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The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: cmp-lg
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The categories of this paper are: eess
9
The categories of this paper are: nlin
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The categories of this paper are: acc-phys
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The categories of this paper are: funct-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: math-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-alg
2
The categories of this paper are: math
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The categories of this paper are: patt-sol