Frank Schoeneman

According to our database, Frank Schoeneman authored at least 7 papers between 2017 and 2020.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2020

Learning Manifolds from Dynamic Process Data.

Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola

Algorithms, 2020

2019

High Performance Approaches for Large-Scale Non-Linear Spectral Dimensionality Reduction of Scientific Data.

Frank Schoeneman

PhD thesis, 2019

Performance of All-Pairs Shortest-Paths Solvers with Apache Spark.

Frank Schoeneman, Jaroslaw Zola

CoRR, 2019

Solving All-Pairs Shortest-Paths Problem in Large Graphs Using Apache Spark.

Frank Schoeneman, Jaroslaw Zola

Proceedings of the 48th International Conference on Parallel Processing, 2019

2018

Scalable Manifold Learning for Big Data with Apache Spark.

Frank Schoeneman, Jaroslaw Zola

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes.

Frank Schoeneman, Varun Chandola, Nils Napp, Olga Wodo, Jaroslaw Zola

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Error Metrics for Learning Reliable Manifolds from Streaming Data.

Frank Schoeneman, Suchismit Mahapatra, Varun Chandola, Nils Napp, Jaroslaw Zola

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017