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ORCIDDaniel M. Dunlavy
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2020 – today
- 2023
[i11]S. Isaac Geronimo Anderson, Keita Teranishi, Daniel M. Dunlavy, Jee Choi:
Analyzing the Performance Portability of Tensor Decomposition. CoRR abs/2307.03276 (2023)- [i10]S. Isaac Geronimo Anderson, Daniel M. Dunlavy
:
Computing Sparse Tensor Decompositions via Chapel and C++/MPI Interoperability without Intermediate I/O. CoRR abs/2310.10872 (2023) - 2022
- [i9]Oscar López, Daniel M. Dunlavy, Richard B. Lehoucq:
Zero-Truncated Poisson Regression for Zero-Inflated Multiway Count Data. CoRR abs/2201.10014 (2022) - [i8]Jeremy M. Myers, Daniel M. Dunlavy:
A Hybrid Method for Tensor Decompositions that Leverages Stochastic and Deterministic Optimization. CoRR abs/2207.14341 (2022) - 2021
- [c13]Jeremy M. Myers, Daniel M. Dunlavy:
Using Computation Effectively for Scalable Poisson Tensor Factorization: Comparing Methods Beyond Computational Efficiency. HPEC 2021: 1-7 - [c12]Stephen L. Olivier, Nathan D. Ellingwood, Jonathan W. Berry, Daniel M. Dunlavy:
Performance Portability of an SpMV Kernel Across Scientific Computing and Data Science Applications. HPEC 2021: 1-8 - 2020
- [c11]Jeremy M. Myers, Daniel M. Dunlavy, Keita Teranishi, David S. Hollman:
Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software. HPEC 2020: 1-7 - [c10]Keita Teranishi, Daniel M. Dunlavy, Jeremy M. Myers, Richard F. Barrett:
SparTen: Leveraging Kokkos for On-node Parallelism in a Second-Order Method for Fitting Canonical Polyadic Tensor Models to Poisson Data. HPEC 2020: 1-7 - [i7]Scott Heidbrink, Kathryn N. Rodhouse, Daniel M. Dunlavy:
Multimodal Deep Learning for Flaw Detection in Software Programs. CoRR abs/2009.04549 (2020) - [i6]Alexis Cooper, Xin Zhou, Scott Heidbrink, Daniel M. Dunlavy:
Using Neural Architecture Search for Improving Software Flaw Detection in Multimodal Deep Learning Models. CoRR abs/2009.10644 (2020) - [i5]Jeremy M. Myers, Daniel M. Dunlavy, Keita Teranishi, David S. Hollman:
Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software: Extended Analysis. CoRR abs/2012.01520 (2020)
2010 – 2019
- 2019
- [i4]Gary J. Saavedra, Kathryn N. Rodhouse, Daniel M. Dunlavy, W. Philip Kegelmeyer:
A Review of Machine Learning Applications in Fuzzing. CoRR abs/1906.11133 (2019) - 2016
- [c9]Michael M. Wolf, Alicia M. Klinvex, Daniel M. Dunlavy:
Advantages to modeling relational data using hypergraphs versus graphs. HPEC 2016: 1-7 - 2013
- [j4]Patricia Crossno, Andrew T. Wilson, Timothy M. Shead, Warren L. Davis IV, Daniel M. Dunlavy:
Topicview: Visual Analysis of Topic Models and their Impact on Document Clustering. Int. J. Artif. Intell. Tools 22(5) (2013) - 2012
- [c8]Brian N. Wylie, Warren L. Davis IV, Danny Dunlavy, Jeffrey Baumes:
Using NoSQL databases for streaming network analysis. LDAV 2012: 121-124 - 2011
- [j3]Daniel M. Dunlavy, Tamara G. Kolda, Evrim Acar:
Temporal Link Prediction Using Matrix and Tensor Factorizations. ACM Trans. Knowl. Discov. Data 5(2): 10:1-10:27 (2011) - [c7]Patricia Crossno, Andrew T. Wilson, Timothy M. Shead, Daniel M. Dunlavy:
TopicView: Visually Comparing Topic Models of Text Collections. ICTAI 2011: 936-943 - [p1]Daniel M. Dunlavy, Tamara G. Kolda, W. Philip Kegelmeyer:
Multilinear Algebra for Analyzing Data with Multiple Linkages. Graph Algorithms in the Language of Linear Algebra 2011: 85-114 - [i3]Evrim Acar, Tamara G. Kolda, Daniel M. Dunlavy:
All-at-once Optimization for Coupled Matrix and Tensor Factorizations. CoRR abs/1105.3422 (2011) - 2010
- [c6]Daniel M. Dunlavy, Timothy M. Shead, Eric T. Stanton:
ParaText: scalable text modeling and analysis. HPDC 2010: 344-347 - [c5]Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda, Morten Mørup:
Scalable Tensor Factorizations with Missing Data. SDM 2010: 701-712 - [i2]Evrim Acar, Tamara G. Kolda, Daniel M. Dunlavy, Morten Mørup:
Scalable Tensor Factorizations for Incomplete Data. CoRR abs/1005.2197 (2010) - [i1]Daniel M. Dunlavy, Tamara G. Kolda, Evrim Acar:
Temporal Link Prediction using Matrix and Tensor Factorizations. CoRR abs/1005.4006 (2010)
2000 – 2009
- 2009
- [c4]Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda:
Link Prediction on Evolving Data Using Matrix and Tensor Factorizations. ICDM Workshops 2009: 262-269 - [c3]Patricia Crossno, Daniel M. Dunlavy, Timothy M. Shead:
LSAView: A tool for visual exploration of latent semantic modeling. IEEE VAST 2009: 83-90 - 2007
- [j2]Daniel M. Dunlavy, Dianne P. O'Leary, John M. Conroy, Judith D. Schlesinger:
QCS: A system for querying, clustering and summarizing documents. Inf. Process. Manag. 43(6): 1588-1605 (2007) - 2005
- [j1]Daniel M. Dunlavy, Dianne P. O'Leary, Dmitri Klimov, D. Thirumalai:
HOPE: A Homotopy Optimization Method for Protein Structure Prediction. J. Comput. Biol. 12(10): 1275-1288 (2005) - 2003
- [c2]Daniel M. Dunlavy, John M. Conroy, Dianne P. O'Leary:
QCS: A Tool for Querying, Clustering, and Summarizing Documents. HLT-NAACL 2003 - [c1]John M. Conroy, Daniel M. Dunlavy, Dianne P. O'Leary:
From TREC to DUC to TREC Again. TREC 2003: 293-302
Coauthor Index
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