Publications

Book Chapters

Multilinear Algebra for Analyzing Data with Multiple Linkages, Daniel M. Dunlavy, Tamara G. Kolda, W. Philip Kegelmeyer, in Graph Algorithms in the Language of Linear Algebra, SIAM, Philadelphia, PA, 2011.  [DOI]  [PDF]

Peer-Reviewed Publications

Performance Portability of an SpMV Kernel Across Scientific Computing and Data Science Applications, Stephen L. Olivier, Nathan D. Ellingwood, Jonathan Berry, Daniel M. Dunlavy, in Proceedings of the IEEE High Performance Extreme Computing Conference (HPEC’21), September 2021.  [DOI]  [PDF]

Using Computation Effectively for Scalable Poisson Tensor Factorization: Comparing Methods Beyond Computational Efficiency, Jeremy Myers, Daniel M. Dunlavy, in Proceedings of the IEEE High Performance Extreme Computing Conference (HPEC’21), September 2021.  [DOI]  [PDF]

Performance-Portable Sparse Tensor Decomposition Kernels on Emerging Parallel Architectures, S. Isaac Geronimo Anderson, Keita Teranishi, Daniel M. Dunlavy, Jee Choi, in Proceedings of the IEEE High Performance Extreme Computing Conference (HPEC’21), September 2021.  [PDF]

SparTen: Leveraging Kokkos for On-node Parallelism in a Second Order Method for Fitting Canonical Polyadic Tensor Models to Poisson Data, Keita Teranishi, Daniel M. Dunlavy, Jeremy Myers, Richard F. Barrett, in Proceedings of the IEEE High Performance Extreme Computing Conference (HPEC’20), September 2020.  [DOI]  [PDF]

Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software, Jeremy Myers, Daniel M. Dunlavy, Keita Teranishi, David S Hollman, in Proceedings of the IEEE High Performance Extreme Computing Conference (HPEC’20), September 2020.  [DOI]  [PDF]

Topic Modeling with Natural Language Processing for Identification of Nuclear Proliferation-Relevant Scientific and Technical Publications, Jonathan Bisila, Daniel M. Dunlavy, Zoe N. Gastelum, Craig D. Ulmer, in Proceedings of the INMM Annual Meeting, July 2020.  [URL]  [PDF]

Advantages to Modeling Relational Data using Hypergraphs versus Graphs, Michael M. Wolf, Alicia M. Klinvex, Daniel M. Dunlavy, in Proceedings of the IEEE High Performance Extreme Computing Conference (HPEC’16), September 2016.  [DOI]  [PDF]

TopicView: Visual Analysis of Topic Models and their Impact on Document Clustering, Patricia Crossno, Andrew Wilson, Timothy Shead, Warren L. Davis IV, Daniel Dunlavy, Journal on Artificial Intelligence Tools, 22(5), 2013.  [DOI]  [PDF]

Using NoSQL Databases for Streaming Network Analysis, Brian Wylie, Daniel Dunlavy, Warren Davis IV, Jeff Baumes, in Proceedings of the IEEE Symposium on Large Scale Data Analysis and Visualization (LDAV), October 2012.  [DOI]  [PDF]

Temporal Link Prediction using Matrix and Tensor Factorizations, Daniel M. Dunlavy, Tamara G. Kolda, Evrim Acar, ACM Transactions on Knowledge Discovery from Data, 5(2):1-27, 2011.  [DOI]  [PDF]

Scalable Tensor Factorizations for Incomplete Data, Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda, Morten Møorup, Chemometrics and Intelligent Laboratory Systems, 106(1):41-56, 2011.  [DOI]  [PDF]

A Scalable Optimization Approach for Fitting Canonical Tensor Decompositions, Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda, Journal of Chemometrics, 25(2):67-86, 2011.  [DOI]  [PDF]

TopicView: Visually Comparing Topic Models of Text Collections, Patricia J. Crossno, Andrew T. Wilson, Timothy M. Shead, Daniel M. Dunlavy, in Proceedings of the 2011 IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Special Session on Text and Web Mining (TWM), November 2011.  [DOI]  [PDF]

TopicView: Understanding Document Relationships Using Latent Dirichlet Allocation Models, Patricia J. Crossno, Andrew T. Wilson, Daniel M. Dunlavy, Timothy M. Shead, in Proceedings of the IEEE Workshop on Interactive Visual Text Analytics for Decision Making, October 2011.  [URL]  [PDF]

All-at-once Optimization for Coupled Matrix and Tensor Factorizations, Evrim Acar, Tamara G. Kolda, Daniel M. Dunlavy, in Proceedings of Mining and Learning with Graphs (MLG), August 2011.  [URL]  [PDF]

ParaText: Scalable Text Modeling and Analysis, Daniel M. Dunlavy, Timothy M. Shead, Eric T. Stanton, in HPDC10: Proceedings of the 19th International ACM Symposium on High Performance Distributed Computing, June 2010.  [DOI]  [PDF]

Scalable Tensor Factorizations with Missing Data, Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda, Morten Mørup, in SDM10: Proceedings of the 2010 SIAM Conference on Data Mining, April 2010.  [DOI]  [PDF]

Link Prediction on Evolving Data using Matrix and Tensor Factorization, Evrim Acar, Tamara G. Kolda, Daniel M. Dunlavy, in LDMTA2009: Proceedings of the 1st Workshop on Large-Scale Data Mining: Theory and Applications, December 2009.  [DOI]  [PDF]

LSAView: A Tool for Visual Exploration of Latent Semantic Modeling, Partricia J. Crossno, Daniel M. Dunlavy, Timothy M. Shead, in IEEE Symposium on Visual Analytics Science and Technology, October 2009.  [DOI]  [PDF]

QCS: A System for Querying, Clustering, and Summarizing Documents, Daniel M. Dunlavy, Dianne P. O’Leary, John M. Conroy, Judith D. Schlesinger, Information Processing \& Management, 43(6), p. 1588-1605, 2007.  [DOI]  [PDF]

Formulations for Surrogate-Based Optimization with Data, Michael S. Eldred, Daniel M. Dunlavy, AIAA-2006-7117, in Proceedings of the 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, September 2006.  [DOI]  [PDF]

HOPE: A Homotopy Optimization Method for Protein Structure Prediction, Daniel M. Dunlavy, Dianne P. O’Leary, Dmitri Klimov, Devarajan Thirumalai, Journal of Computation Biology, 12(10):1275-1288, December 2005.   [DOI]  [PDF]

Structure Preserving Algorithms for Perplectic Eigenproblems, D. Steven Mackey, Niloufer Mackey, Daniel M. Dunlavy, Electronic Journal of Linear Algebra, 13:10-39, 2005.  [DOI]  [PDF]

From TREC to DUC to TREC Again, John M. Conroy, Dianne P. O’Leary, Daniel M. Dunlavy, in Proceedings of the Twelfth Text Retrieval Conference (TREC), 2004.  [URL]  [PDF]

Performance of a Three-Stage System for Multi-Document Summarization, Daniel M. Dunlavy, John M. Conroy, Judith D. Schlesinger, Sarah A. Goodman, Mary E. Okurowski, Dianne P. O’Leary, Hans van Halteren, in Proceedings of the Document Understanding Conference (DUC), 2003.  [URL]  [PDF]

Other Conference and Workshop Proceedings

CPOPT: Optimization for Fitting CANDECOMP/PARAFAC Models, Evrim Acar, Tamara G. Kolda, Daniel M. Dunlavy, in CASTA 2008: Workshop on Computational Algebraic Statistics, Theories and Applications, December 2008. [PDF]

QCS: A Tool for Querying, Clustering, and Summarizing Documents, Daniel M. Dunlavy, John M. Conroy, Dianne P. O’Leary, in Proceedings of the HLT-NAACL Conference, June 2003. [URL]

Technical Reports

Document Retrieval and Ranking using Similarity Graph Mean Hitting Times, Daniel M. Dunlavy, Peter A. Chew, Technical Report Number SAND2021-15731, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, December 2021.  [PDF]

Assessing the Interdisciplinarity of Scientific Research Proposals using Text Analysis Methods, Jonathan Bisila, Erica Douglas, Daniel M. Dunlavy, Technical Report Number SAND2021-14786, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, November 2021.

Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software: Extended Analysis, Jeremy M. Myers, Daniel M. Dunlavy, Keita Teranishi, D. S. Hollman, arXiv:2012.01520, December 2020.  [URL]

LDRD Final Report: Joint Analysis of Program Data Representations using Machine Learning for Improved Software Assurance and Development Capabilities, Scott Heidbrink, Kathryn N. Rodhouse, Daniel M. Dunlavy, Alexis Cooper, Xin Zhou, Technical Report Number SAND2020-10150, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, September 2020.  [PDF]

Using Neural Architecture Search for Improving Software Flaw Detection in Multimodal Deep Learning Models, Alexis Cooper, Xin Zhou, Scott Heidbrink, Daniel M. Dunlavy, arXiv:2009.10644, September 2020.  [URL]

Multimodal Deep Learning for Flaw Detection in Software Programs, Scott Heidbrink, Kathryn N. Rodhouse, Daniel M. Dunlavy, arXiv:2009.04549,September 2020.  [URL]

LDRD Final Report: Modeling Complex Relationships in Large-Scale Data using Hypergraphs, Daniel M. Dunlavy, Fulton Wang, Michael Wolf, Nathan D. Ellingwood, Technical Report Number SAND2019-14159, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, November 2019.  [PDF]

A Review of Machine Learning Applications in Fuzzing, Gary J Saavedra, Kathryn N Rodhouse, Daniel M Dunlavy, W. Philip Kegelmeyer, arXiv:1906.11133, October 2019.  [URL]

Embedding Python for In-Situ Analysis, Timothy M. Shead, Konduri Aditya, Hemanth Kolla, Daniel M. Dunlavy, W. Philip Kegelmeyer, Warren L. Davis IV, Technical Report Number SAND2018-9009, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, August 2018.  [PDF]

Using Machine Learning in Adversarial Environments, Warren L. Davis IV, Daniel M. Dunlavy, Yevgeniy Vorobeychik, Karin Butler, Chris Forsythe, Matt Letter, Nichole Murchison, Kevin Nauer, Technical Report Number SAND2016-10426, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, October 2016.  [PDF]

Constrained Versions of DEDICOM for Use in Unsupervised Part-Of-Speech Tagging, Daniel M. Dunlavy, Peter A. Chew, Technical Report Number SAND2016-4520, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, May 2016.  [PDF]

Tensor Toolbox: Wrapping to Python using SWIG, Matthew G. Peterson, Daniel M. Dunlavy, Technical Report Number SAND2015-3829O, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, December 2014.  [PDF]

Hybrid Methods for Cybersecurity Analysis LDRD Final Report, Warren L. Davis IV, Daniel M. Dunlavy, Technical Report Number SAND2014-0446, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, January 2014.  [PDF]

Network and Ensemble Enabled Entity Extraction in Informal Text (NEEEEIT) Final Report, W. Philip Kegelmeyer, Timothy M. Shead, Daniel M. Dunlavy, Technical Report Number SAND2013-9344, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, September 2013.  [PDF]

ParaText—Scalable Solutions for Processing and Searching Very Large Document Collections: Final LDRD Report, Daniel M. Dunlavy, Timothy M. Shead, Patricia J. Crossno, Eric T. Stanton, Technical Report Number SAND2010-6269, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, September 2010.  [PDF]

Poblano v1.0: A Matlab Toolbox for Gradient-Based Optimization, Daniel M. Dunlavy, Tamara G. Kolda, Evrim Acar, Technical Report Number SAND2010-1422, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, March 2010.  [PDF]

Scalable Tensor Factorizations with Missing Data, Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda, Morton Mørup, Technical Report Number SAND2009-6764, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, October 2009.  [PDF]

Relationships Between Accuracy and Diversity in Heterogeneous Ensemble Classifiers, Sean A. Gilpin, Daniel M. Dunlavy, Technical Report Number SAND2009-6940C, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, September 2009.  [PDF]

Semisupervised Named Entity Recognition, Taylor P. Turpen, Daniel M. Dunlavy, Technical Report Number SAND2010-3083P, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, September 2009.  [PDF]

An Optimization Approach for Fitting Canonical Tensor Decompositions, Evrim Acar, Tamara G. Kolda, Daniel M. Dunlavy, Technical Report Number SAND2009-0857, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, February 2009.  [PDF]

Mathematical Challenges in Cybersecurity, Daniel M. Dunlavy, Bruce A. Hendrickson, Tamara G. Kolda, Technical Report Number SAND2009-0805, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, February 2009.  [PDF]

Heterogeneous Ensemble Classification, Sean A. Gilpin, Daniel M. Dunlavy, Technical Report Number SAND2009-0203P, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, January 2009.  [PDF]

Trilinos CMake Evaluation, Roscoe A. Bartlett, Daniel M. Dunlavy, Esteban J. Guillen, Tim Shead, Technical Report Number SAND2008-7593, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, November 2008.  [PDF]

Proceedings of the 2008 Sandia Workshop on Data Mining and Data Analysis, James M. Brandt, Daniel M. Dunlavy, Ann C. Gentile, Technical Report Number SAND2008-6109, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, September 2008.  [PDF]

Yucca Mountain LSN Archive Assistant, Justin D. Basilico, Daniel M. Dunlavy, Stephen J. Verzi, Travis L. Bauer, Wendy Shaneyfelt, Technical Report Number SAND2008-1622, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, March 2008.  [PDF]

QCS: A System for Querying, Clustering, and Summarizing Documents, Daniel M. Dunlavy, Dianne P. O’Leary, John M. Conroy, Judith D. Schlesinger, Technical Report Number SAND2006-5000, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, October 2006.  [PDF]

DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 4.0 Users Manual, Michael S. Eldred, Shannon L. Brown, Brian M. Adams, Daniel M. Dunlavy, David M. Gay, Laura P. Swiler, Anthony A. Giunta, William E. Hart, Jean-PaulWatson, John P. Eddy, Josh D. Griffin, Patty D. Hough, Tammy G. Kolda, Monica L. Martinez-Canales, Pamela J.Williams, Technical Report Number SAND2006-6637, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, October 2006.  [PDF]

DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 4.0 Developers Manual, Michael S. Eldred, Shannon L. Brown, Brian M. Adams, Daniel M. Dunlavy, David M. Gay, Laura P. Swiler, Anthony A. Giunta, William E. Hart, Jean-PaulWatson, John P. Eddy, Josh D. Griffin, Patty D. Hough, Tammy G. Kolda, Monica L. Martinez-Canales, Pamela J.Williams, Technical Report Number SAND2006-4056, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, September 2006.  [PDF]

DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 4.0 Reference Manual, Michael S. Eldred, Shannon L. Brown, Brian M. Adams, Daniel M. Dunlavy, David M. Gay, Laura P. Swiler, Anthony A. Giunta, William E. Hart, Jean-PaulWatson, John P. Eddy, Josh D. Griffin, Patty D. Hough, Tammy G. Kolda, Monica L. Martinez-Canales, Pamela J.Williams, Technical Report Number SAND2006-4055, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, September 2006.  [PDF]

Multilinear Algebra for Analyzing Data with Multiple Linkages, Daniel M. Dunlavy, Tamara G. Kolda, W. Philip Kegelmeyer, Technical Report Number SAND2006-2079, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, April 2006.  [PDF]

Homotopy Optimization Methods for Global Optimization, Daniel M. Dunlavy, Dianne P. O’Leary, Technical Report Number SAND2005-7495, Sandia National Laboratories, Albuquerque, NM and Livermore, CA, December 2005.  [PDF]

Structure Preserving Algorithms for Perplectic Eigenproblems, D. Steven Mackey, Niloufer Mackey, Daniel M. Dunlavy, Numerical Analysis Report No. 427, Manchester Centre for Computational Mathematics, Manchester, England, May 2003.  [PDF]

Numerical Steady-State Solutions of Non-Linear DAE’s Arising in RF Communication Circuit Design, Danny Dunlavy, Sookhyung Joo, Runchang Lin, Roummel Marcia, Aurelia Minut, Jianzhong Sun, Technical Report Number 1752-1, Institute for Mathematics and Its Applications (IMA) Preprint Series, February 2001.  [PDF]

Expository Articles

Survival Guide for Graduate Students in Scientific Computation, Danny Dunlavy, Chris Danforth, Aaron Lott, Bob Shuttleworth, Applied Mathematics and Scientific Computation Program, University of Maryland, Fall 2004.   [PDF]

Dissertation and Thesis

Homotopy Optimization Methods and Protein Structure Prediction, Daniel M. Dunlavy, Ph.D. Dissertation, Applied Mathematics and Scientific Computation Program, University of Maryland, College Park, August 2005.  [PDF]

QCS: An Information Retrieval System for Improving Efficiency in Scientific Literature Searches, Daniel M. Dunlavy, M.S. Thesis, Applied Mathematics and Scientific Computation Program, University of Maryland, College Park, August 2003.  [PDF]