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ParMOO: A Python library for parallel multiobjectivesimulation optimization

https://doi.org/10.21105/joss.04468

Chang, Tyler H. ; Wild, Stefan M. ( February 2023 , Journal of Open Source Software)

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Co-Scale Conv-Attentional Image Transformers

https://doi.org/10.1109/ICCV48922.2021.00983

Xu, Weijian ; Xu, Yifan ; Chang, Tyler ; Tu, Zhuowen ( October 2021 , International Conference on Computer Vision)

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Design strategies and approximation methods for high-performance computing variability management

https://doi.org/10.1080/00224065.2022.2035285

Wang, Yueyao ; Xu, Li ; Hong, Yili ; Pan, Rong ; Chang, Tyler ; Lux, Thomas ; Bernard, Jon ; Watson, Layne ; Cameron, Kirk ( February 2022 , Journal of Quality Technology)

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Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models

https://doi.org/10.18653/v1/2021.acl-long.333

Chang, Tyler A. ; Xu, Yifan ; Xu, Weijian ; Tu, Zhuowen ( August 2021 , Proceedings of the conference Association for Computational Linguistics Meeting)

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Prediction of high-performance computing input/output variability and its application to optimization for system configurations

https://doi.org/10.1080/08982112.2020.1866203

Xu, Li ; Lux, Thomas ; Chang, Tyler ; Li, Bo ; Hong, Yili ; Watson, Layne ; Butt, Ali ; Yao, Danfeng ; Cameron, Kirk ( April 2021 , Quality Engineering)
null (Ed.)
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Algorithm 1012: DELAUNAYSPARSE: Interpolation via a Sparse Subset of the Delaunay Triangulation in Medium to High Dimensions

https://doi.org/10.1145/3422818

Chang, Tyler H. ; Watson, Layne T. ; Lux, Thomas C. ; Butt, Ali R. ; Cameron, Kirk W. ; Hong, Yili ( November 2020 , ACM Transactions on Mathematical Software)
null (Ed.)
DELAUNAYSPARSE contains both serial and parallel codes written in Fortran 2003 (with OpenMP) for performing medium- to high-dimensional interpolation via the Delaunay triangulation. To accommodate the exponential growth in the size of the Delaunay triangulation in high dimensions, DELAUNAYSPARSE computes only a sparse subset of the complete Delaunay triangulation, as necessary for performing interpolation at the user specified points. This article includes algorithm and implementation details, complexity and sensitivity analyses, usage information, and a brief performance study.
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Modeling I/O performance variability in high-performance computing systems using mixture distributions

https://doi.org/10.1016/j.jpdc.2020.01.005

Xu, Li ; Wang, Yueyao ; Lux, Thomas ; Chang, Tyler ; Bernard, Jon ; Li, Bo ; Hong, Yili ; Cameron, Kirk ; Watson, Layne ( May 2020 , Journal of Parallel and Distributed Computing)

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Computing the Umbrella Neighbourhood of a Vertex in the Delaunay Triangulation and a Single Voronoi Cell in Arbitrary Dimension

https://doi.org/10.1109/SECON.2018.8479003

Chang, Tyler H. ; Watson, Layne T. ; Lux, Thomas C. ; Raghvendra, Sharath ; Li, Bo ; Xu, Li ; Butt, Ali R. ; Cameron, Kirk W. ; Hong, Yili ( April 2018 , Proc. IEEE Southeastcon 2018)

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A polynomial time algorithm for multivariate interpolation in arbitrary dimension via the Delaunay triangulation

https://doi.org/10.1145/3190645.3190680

Chang, Tyler H. ; Watson, Layne T. ; Lux, Thomas C. ; Li, Bo ; Xu, Li ; Butt, Ali R. ; Cameron, Kirk W. ; Hong, Yili ( January 2018 , Proceedings ACM Southeast 2018 Conf.)

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Nonparametric Distribution Models for Predicting and Managing Computational Performance Variability

https://doi.org/10.1109/SECON.2018.8478814

Lux, Thomas C. ; Watson, Layne T. ; Chang, Tyler H. ; Bernard, Jon ; Li, Bo ; Yu, Xiaodong ; Xu, Li ; Back, Godmar ; Butt, Ali R. ; Cameron, Kirk W. ; et al ( April 2018 , Proceedings of IEEE Southeastcon 2018)

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