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Erik Skau
Person information
- affiliation: Los Alamos National Laboratories, NM, USA
- affiliation (PhD): North Carolina State University, Raleigh, NC, USA
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2020 – today
- 2024
- [j13]Ismael Boureima, Manish Bhattarai, Maksim Ekin Eren, Erik Skau, Philip Romero, Stephan J. Eidenbenz, Boian S. Alexandrov:
Distributed out-of-memory NMF on CPU/GPU architectures. J. Supercomput. 80(3): 3970-3999 (2024) - [j12]Ismael Boureima, Manish Bhattarai, Maksim Ekin Eren, Erik Skau, Philip Romero, Stephan J. Eidenbenz, Boian S. Alexandrov:
Correction to: Distributed out-of-memory NMF on CPU/GPU architectures. J. Supercomput. 80(4): 5731-5732 (2024) - [c11]Duc P. Truong
, Erik Skau
Accelerated Dempster Shafer Using Tensor Train Representation. BELIEF 2024: 283-292 - [i10]Minh Vu, Ben Nebgen, Erik Skau, Geigh Zollicoffer, Juan Castorena, Kim Ø. Rasmussen, Boian S. Alexandrov, Manish Bhattarai:
LaFA: Latent Feature Attacks on Non-negative Matrix Factorization. CoRR abs/2408.03909 (2024) - 2023
- [j11]Maksim Ekin Eren, Juston S. Moore, Erik Skau, Elisabeth Moore, Manish Bhattarai, Gopinath Chennupati, Boian S. Alexandrov:
General-purpose Unsupervised Cyber Anomaly Detection via Non-negative Tensor Factorization. DTRAP 4(1): 6:1-6:28 (2023) - [j10]Manish Bhattarai
Distributed non-negative RESCAL with automatic model selection for exascale data. J. Parallel Distributed Comput. 179: 104709 (2023) - [c10]Erik Skau, Cassandra Armstrong, Duc P. Truong, David Gerts, Kari Sentz:
Open world Dempster-Shafer using complementary sets. ISIPTA 2023: 438-449 - 2022
- [j9]Boian S. Alexandrov, Derek F. DeSantis, Gianmarco Manzini, Erik W. Skau:
Nonnegative canonical tensor decomposition with linear constraints: nnCANDELINC. Numer. Linear Algebra Appl. 29(6) (2022) - [j8]Derek DeSantis, Erik Skau, Duc Phan Minh Truong
Factorization of Binary Matrices: Rank Relations, Uniqueness and Model Selection of Boolean Decomposition. ACM Trans. Knowl. Discov. Data 16(6): 112:1-112:24 (2022) - [i9]Valentin G. Stanev, Erik Skau, Ichiro Takeuchi, Boian S. Alexandrov:
Topic Analysis of Superconductivity Literature by Semantic Non-negative Matrix Factorization. CoRR abs/2201.00687 (2022) - [i8]Manish Bhattarai, Namita Kharat, Erik Skau, Benjamin T. Nebgen, Hristo N. Djidjev, Sanjay V. Rajopadhye, James P. Smith, Boian S. Alexandrov:
Distributed non-negative RESCAL with Automatic Model Selection for Exascale Data. CoRR abs/2202.09512 (2022) - [i7]Ismael Boureima, Manish Bhattarai, Maksim Ekin Eren, Erik Skau, Philip Romero, Stephan J. Eidenbenz, Boian S. Alexandrov:
Distributed Out-of-Memory NMF of Dense and Sparse Data on CPU/GPU Architectures with Automatic Model Selection for Exascale Data. CoRR abs/2202.09518 (2022) - [i6]Erik Skau, Andrew Hollis, Stephan J. Eidenbenz, Kim Ø. Rasmussen, Boian S. Alexandrov:
Process Modeling, Hidden Markov Models, and Non-negative Tensor Factorization with Model Selection. CoRR abs/2210.01060 (2022) - 2021
- [j7]Duc Phan Minh Truong
Boolean Matrix Factorization via Nonnegative Auxiliary Optimization. IEEE Access 9: 117169-117177 (2021) - [j6]Raviteja Vangara
Finding the Number of Latent Topics With Semantic Non-Negative Matrix Factorization. IEEE Access 9: 117217-117231 (2021) - [j5]Giancarlo Sanchez
Automatic Model Determination for Quaternion NMF. IEEE Access 9: 152243-152249 (2021) - [c9]Gianmarco Manzini, Erik Skau, Duc Phan Minh Truong, Raviteja Vangara:
Nonnegative Tensor-Train Low-Rank Approximations of the Smoluchowski Coagulation Equation. LSSC 2021: 342-350 - [c8]Valentin G. Stanev, Erik Skau, Ichiro Takeuchi, Boian S. Alexandrov:
Topic Analysis of Superconductivity Literature by Semantic Non-negative Matrix Factorization. LSSC 2021: 359-366 - [i5]Duc Phan Minh Truong, Erik Skau, Derek DeSantis, Boian S. Alexandrov:
Boolean Matrix Factorization via Nonnegative Auxiliary Optimization. CoRR abs/2106.04708 (2021) - 2020
- [j4]Hector Carrillo-Cabada
An Out of Memory tSVD for Big-Data Factorization. IEEE Access 8: 107749-107759 (2020) - [j3]Duc Phan Minh Truong
Determination of latent dimensionality in international trade flow. Mach. Learn. Sci. Technol. 1(4): 45017 (2020) - [j2]Gopinath Chennupati
Distributed non-negative matrix factorization with determination of the number of latent features. J. Supercomput. 76(9): 7458-7488 (2020) - [c7]Manish Bhattarai
Distributed Non-Negative Tensor Train Decomposition. HPEC 2020: 1-10 - [c6]Raviteja Vangara, Erik Skau, Gopinath Chennupati, Hristo N. Djidjev, Thomas Tierney, James P. Smith, Manish Bhattarai
Semantic Nonnegative Matrix Factorization with Automatic Model Determination for Topic Modeling. ICMLA 2020: 328-335 - [i4]Duc Phan Minh Truong, Erik Skau, Vladimir I. Valtchinov, Boian S. Alexandrov:
Determination of Latent Dimensionality in International Trade Flow. CoRR abs/2003.00129 (2020) - [i3]Manish Bhattarai, Gopinath Chennupati, Erik Skau, Raviteja Vangara, Hristo N. Djidjev, Boian S. Alexandrov:
Distributed Non-Negative Tensor Train Decomposition. CoRR abs/2008.01340 (2020) - [i2]Derek DeSantis, Erik Skau, Boian S. Alexandrov:
Factorizations of Binary Matrices - Rank Relations and the Uniqueness of Boolean Decompositions. CoRR abs/2012.10496 (2020)
2010 – 2019
- 2019
- [i1]Boian S. Alexandrov, Derek DeSantis, Gianmarco Manzini, Erik Skau:
Nonnegative Canonical Polyadic Decomposition with Rank Deficient Factors. CoRR abs/1909.07570 (2019) - 2018
- [j1]Han Wang
Fusing Heterogeneous Data: A Case for Remote Sensing and Social Media. IEEE Trans. Geosci. Remote. Sens. 56(12): 6956-6968 (2018) - [c5]Erik Skau, Cristina Garcia-Cardona
Tomographic Reconstruction Via 3D Convolutional Dictionary Learning. IVMSP 2018: 1-5 - [c4]Erik Skau, Brendt Wohlberg
A Fast Parallel Algorithm for Convolutional Sparse Coding. IVMSP 2018: 1-5 - 2017
- [c3]Shahin Mahdizadehaghdam, Liyi Dai, Hamid Krim, Erik Skau, Han Wang:
Image classification: A hierarchical dictionary learning approach. ICASSP 2017: 2597-2601 - 2016
- [c2]Erik Skau, Brendt Wohlberg
Pansharpening via coupled triple factorization dictionary learning. ICASSP 2016: 1234-1237 - [c1]Sally Ghanem, Erik Skau, Hamid Krim, Hamilton Scott Clouse, Wesam A. Sakla:
Non-parametric bounds on the nearest neighbor classification accuracy based on the Henze-Penrose metric. ICIP 2016: 1364-1368
Coauthor Index
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last updated on 2024-11-20 20:58 CET by the dblp team
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