3 papers
cs.DC2019
Solving All-Pairs Shortest-Paths Problem in Large Graphs Using Apache Spark
Frank Schoeneman, Jaroslaw Zola
Algorithms for computing All-Pairs Shortest-Paths (APSP) are critical building blocks underlying many practical applications. The standard sequential algorithms, such as Floyd-Wars…
cs.DC2018
Scalable Manifold Learning for Big Data with Apache Spark
Frank Schoeneman, Jaroslaw Zola
Non-linear spectral dimensionality reduction methods, such as Isomap, remain important technique for learning manifolds. However, due to computational complexity, exact manifold le…
stat.ML2018
Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes
Frank Schoeneman, Varun Chandola, Nils Napp +2
Scientific and engineering processes deliver massive high-dimensional data sets that are generated as non-linear transformations of an initial state and few process parameters. Map…