1 citations · 4 across the 8 of their papers we have counts for
9 papers
An Analysis of the Johnson-Lindenstrauss Lemma with the Bivariate Gamma Distribution
Jason Bernstein, Alec M. Dunton, Benjamin W. Priest
Probabilistic proofs of the Johnson-Lindenstrauss lemma imply that random projection can reduce the dimension of a data set and approximately preserve pairwise distances. If a dist…
Scalable Gaussian Process Hyperparameter Optimization via Coverage Regularization
Killian Wood, Alec M. Dunton, Amanda Muyskens +1
Gaussian processes (GPs) are Bayesian non-parametric models popular in a variety of applications due to their accuracy and native uncertainty quantification (UQ). Tuning GP hyperpa…
Light curve completion and forecasting using fast and scalable Gaussian processes (MuyGPs)
Imène R. Goumiri, Alec M. Dunton, Amanda L. Muyskens +2
Temporal variations of apparent magnitude, called light curves, are observational statistics of interest captured by telescopes over long periods of time. Light curves afford the e…
Fast Gaussian Process Posterior Mean Prediction via Local Cross Validation and Precomputation
Alec M. Dunton, Benjamin W. Priest, Amanda Muyskens
Gaussian processes (GPs) are Bayesian non-parametric models useful in a myriad of applications. Despite their popularity, the cost of GP predictions (quadratic storage and cubic co…
Deterministic matrix sketches for low-rank compression of high-dimensional simulation data
Alec Michael Dunton, Alireza Doostan
Matrices arising in scientific applications frequently admit linear low-rank approximations due to smoothness in the physical and/or temporal domain of the problem. In large-scale…
Task-parallel in-situ temporal compression of large-scale computational fluid dynamics data
Heather Pacella, Alec Dunton, Alireza Doostan +1
Present day computational fluid dynamics simulations generate extremely large amounts of data, sometimes on the order of TB/s. Often, a significant fraction of this data is discard…
Mixed precision matrix interpolative decompositions for model reduction
Alec Michael Dunton, Alyson Fox
Renewed interest in mixed-precision algorithms has emerged due to growing data capacity and bandwidth concerns, as well as the advancement of GPUs, which enable significant speedup…
Scaling Graph Clustering with Distributed Sketches
Benjamin W. Priest, Alec Dunton, Geoffrey Sanders
The unsupervised learning of community structure, in particular the partitioning vertices into clusters or communities, is a canonical and well-studied problem in exploratory graph…
Pass-efficient methods for compression of high-dimensional turbulent flow data
Alec M. Dunton, Lluís Jofre, Gianluca Iaccarino +1
The future of high-performance computing, specifically on future Exascale computers, will presumably see memory capacity and bandwidth fail to keep pace with data generated, for in…