Erik Skau

According to our database, Erik Skau authored at least 31 papers between 2016 and 2024.

Collaborative distances:

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

2024

Generating Hidden Markov Models from Process Models Through Nonnegative Tensor Factorization.

Erik Skau, Andrew Hollis, Stephan J. Eidenbenz, Kim Ø. Rasmussen, Boian S. Alexandrov

ACM Trans. Model. Comput. Simul., October, 2024

Correction to: Distributed out-of-memory NMF on CPU/GPU architectures.

Ismael Boureima, Manish Bhattarai, Maksim Ekin Eren, Erik Skau, Philip Romero, Stephan J. Eidenbenz, Boian S. Alexandrov

J. Supercomput., March, 2024

Distributed out-of-memory NMF on CPU/GPU architectures.

Ismael Boureima, Manish Bhattarai, Maksim Ekin Eren, Erik Skau, Philip Romero, Stephan J. Eidenbenz, Boian S. Alexandrov

J. Supercomput., February, 2024

LaFA: Latent Feature Attacks on Non-negative Matrix Factorization.

Minh N. Vu, Ben Nebgen, Erik Skau, Geigh Zollicoffer, Juan Castorena, Kim Ø. Rasmussen, Boian S. Alexandrov, Manish Bhattarai

CoRR, 2024

Accelerated Dempster Shafer Using Tensor Train Representation.

Duc P. Truong, Erik Skau, Cassandra Armstrong, Kari Sentz

Proceedings of the Belief Functions: Theory and Applications, 2024

2023

Distributed non-negative RESCAL with automatic model selection for exascale data.

Manish Bhattarai, Namita Kharat, Ismael Boureima, Erik Skau, Benjamin T. Nebgen, Hristo N. Djidjev, Sanjay V. Rajopadhye, James P. Smith, Boian S. Alexandrov

J. Parallel Distributed Comput., September, 2023

General-purpose Unsupervised Cyber Anomaly Detection via Non-negative Tensor Factorization.

Maksim Ekin Eren, Juston S. Moore, Erik Skau, Elisabeth Moore, Manish Bhattarai, Gopinath Chennupati, Boian S. Alexandrov

DTRAP, 2023

Open world Dempster-Shafer using complementary sets.

Erik Skau, Cassandra Armstrong, Duc P. Truong, David Gerts, Kari Sentz

Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2023

2022

Factorization of Binary Matrices: Rank Relations, Uniqueness and Model Selection of Boolean Decomposition.

Derek DeSantis, Erik Skau, Duc Phan Minh Truong, Boian S. Alexandrov

ACM Trans. Knowl. Discov. Data, 2022

Nonnegative canonical tensor decomposition with linear constraints: nnCANDELINC.

Boian S. Alexandrov, Derek F. DeSantis, Gianmarco Manzini, Erik W. Skau

Numer. Linear Algebra Appl., 2022

Process Modeling, Hidden Markov Models, and Non-negative Tensor Factorization with Model Selection.

Erik Skau, Andrew Hollis, Stephan J. Eidenbenz, Kim Ø. Rasmussen, Boian S. Alexandrov

CoRR, 2022

Distributed Out-of-Memory NMF of Dense and Sparse Data on CPU/GPU Architectures with Automatic Model Selection for Exascale Data.

Ismael Boureima, Manish Bhattarai, Maksim Ekin Eren, Erik Skau, Philip Romero, Stephan J. Eidenbenz, Boian S. Alexandrov

CoRR, 2022

Distributed non-negative RESCAL with Automatic Model Selection for Exascale Data.

Manish Bhattarai, Namita Kharat, Erik Skau, Benjamin T. Nebgen, Hristo N. Djidjev, Sanjay V. Rajopadhye, James P. Smith, Boian S. Alexandrov

CoRR, 2022

2021

Finding the Number of Latent Topics With Semantic Non-Negative Matrix Factorization.

Raviteja Vangara, Manish Bhattarai, Erik Skau, Gopinath Chennupati, Hristo N. Djidjev, Thomas Tierney, James P. Smith, Valentin G. Stanev, Boian S. Alexandrov

IEEE Access, 2021

Boolean Matrix Factorization via Nonnegative Auxiliary Optimization.

Duc Phan Minh Truong, Erik Skau, Derek DeSantis, Boian S. Alexandrov

IEEE Access, 2021

Automatic Model Determination for Quaternion NMF.

Giancarlo Sanchez, Erik Skau, Boian S. Alexandrov

IEEE Access, 2021

Topic Analysis of Superconductivity Literature by Semantic Non-negative Matrix Factorization.

Valentin G. Stanev, Erik Skau, Ichiro Takeuchi, Boian S. Alexandrov

Proceedings of the Large-Scale Scientific Computing - 13th International Conference, 2021

Nonnegative Tensor-Train Low-Rank Approximations of the Smoluchowski Coagulation Equation.

Gianmarco Manzini, Erik Skau, Duc Phan Minh Truong, Raviteja Vangara

Proceedings of the Large-Scale Scientific Computing - 13th International Conference, 2021

2020

Distributed non-negative matrix factorization with determination of the number of latent features.

Gopinath Chennupati, Raviteja Vangara, Erik Skau, Hristo N. Djidjev, Boian S. Alexandrov

J. Supercomput., 2020

Determination of latent dimensionality in international trade flow.

Duc Phan Minh Truong, Erik Skau, Vladimir I. Valtchinov, Boian S. Alexandrov

Mach. Learn. Sci. Technol., 2020

Factorizations of Binary Matrices - Rank Relations and the Uniqueness of Boolean Decompositions.

Derek DeSantis, Erik Skau, Boian S. Alexandrov

CoRR, 2020

An Out of Memory tSVD for Big-Data Factorization.

Hector Carrillo-Cabada, Erik Skau, Gopinath Chennupati, Boian S. Alexandrov, Hristo N. Djidjev

IEEE Access, 2020

Semantic Nonnegative Matrix Factorization with Automatic Model Determination for Topic Modeling.

Raviteja Vangara, Erik Skau, Gopinath Chennupati, Hristo N. Djidjev, Thomas Tierney, James P. Smith, Manish Bhattarai, Valentin G. Stanev, Boian S. Alexandrov

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

Distributed Non-Negative Tensor Train Decomposition.

Manish Bhattarai, Gopinath Chennupati, Erik Skau, Raviteja Vangara, Hristo N. Djidjev, Boian S. Alexandrov

Proceedings of the 2020 IEEE High Performance Extreme Computing Conference, 2020

2019

Nonnegative Canonical Polyadic Decomposition with Rank Deficient Factors.

Boian S. Alexandrov, Derek DeSantis, Gianmarco Manzini, Erik Skau

CoRR, 2019

2018

Fusing Heterogeneous Data: A Case for Remote Sensing and Social Media.

Han Wang, Erik Skau, Hamid Krim, Guido Cervone

IEEE Trans. Geosci. Remote. Sens., 2018

A Fast Parallel Algorithm for Convolutional Sparse Coding.

Erik Skau, Brendt Wohlberg

Proceedings of the 13th IEEE Image, Video, and Multidimensional Signal Processing Workshop, 2018

Tomographic Reconstruction Via 3D Convolutional Dictionary Learning.

Erik Skau, Cristina Garcia-Cardona

Proceedings of the 13th IEEE Image, Video, and Multidimensional Signal Processing Workshop, 2018

2017

Image classification: A hierarchical dictionary learning approach.

Shahin Mahdizadehaghdam, Liyi Dai, Hamid Krim, Erik Skau, Han Wang

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016

Non-parametric bounds on the nearest neighbor classification accuracy based on the Henze-Penrose metric.

Sally Ghanem, Erik Skau, Hamid Krim, Hamilton Scott Clouse, Wesam A. Sakla

Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

Pansharpening via coupled triple factorization dictionary learning.

Erik Skau, Brendt Wohlberg, Hamid Krim, Liyi Dai

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016