Stefan M. Wild

Orcid: 0000-0002-6099-2772

  • Mathematics and Computer Science Division, Argonne National Laboratory

According to our database1, Stefan M. Wild authored at least 82 papers between 2004 and 2024.

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In proceedings 
PhD thesis 


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Stochastic average model methods.
Comput. Optim. Appl., June, 2024

Sequential Bayesian Experimental Design for Calibration of Expensive Simulation Models.
Technometrics, April, 2024

Constructing a Simulation Surrogate with Partially Observed Output.
Technometrics, 2024

Portable, heterogeneous ensemble workflows at scale using libEnsemble.
CoRR, 2024

Research Spotlights.
SIAM Rev., November, 2023

Adaptive sampling quasi-Newton methods for zeroth-order stochastic optimization.
Math. Program. Comput., June, 2023

DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection.
Mach. Learn. Sci. Technol., June, 2023

Modeling approaches for addressing unrelaxable bound constraints with unconstrained optimization methods.
Optim. Lett., April, 2023

ParMOO: A Python library for parallel multiobjective simulation optimization.
J. Open Source Softw., February, 2023

A framework for fully autonomous design of materials via multiobjective optimization and active learning: challenges and next steps.
CoRR, 2023

Designing a Framework for Solving Multiobjective Simulation Optimization Problems.
CoRR, 2023

libEnsemble: A Library to Coordinate the Concurrent Evaluation of Dynamic Ensembles of Calculations.
IEEE Trans. Parallel Distributed Syst., 2022

DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification.
Mach. Learn. Sci. Technol., 2022

Numerical evidence against advantage with quantum fidelity kernels on classical data.
CoRR, 2022

Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection.
CoRR, 2022

Bandwidth Enables Generalization in Quantum Kernel Models.
CoRR, 2022

Tuning Multigrid Methods with Robust Optimization and Local Fourier Analysis.
SIAM J. Sci. Comput., 2021

A method for convex black-box integer global optimization.
J. Glob. Optim., 2021

Sequential Learning of Active Subspaces.
J. Comput. Graph. Stat., 2021

Importance of Kernel Bandwidth in Quantum Machine Learning.
CoRR, 2021

Robustness of deep learning algorithms in astronomy - galaxy morphology studies.
CoRR, 2021

Randomized Algorithms for Scientific Computing (RASC).
CoRR, 2021

Emerging Frameworks for Advancing Scientific Workflows Research, Development, and Education.
Proceedings of the 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), 2021

Scalable Statistical Inference of Photometric Redshift via Data Subsampling.
Proceedings of the Computational Science - ICCS 2021, 2021

Hierarchical Analysis of Halo Center in Cosmology.
Proceedings of the Computational Science - ICCS 2021, 2021

Derivative-free robust optimization by outer approximations.
Math. Program., 2020

A survey of nonlinear robust optimization.
INFOR Inf. Syst. Oper. Res., 2020

Tuning Multigrid Methods with Robust Optimization.
CoRR, 2020

Pufferscale: Rescaling HPC Data Services for High Energy Physics Applications.
Proceedings of the 20th IEEE/ACM International Symposium on Cluster, 2020

Simultaneous Sensing Error Recovery and Tomographic Inversion Using an Optimization-Based Approach.
SIAM J. Sci. Comput., 2019

Derivative-free optimization methods.
Acta Numer., 2019

Scalable reinforcement-learning-based neural architecture search for cancer deep learning research.
Proceedings of the International Conference for High Performance Computing, 2019

Adaptive Learning for Concept Drift in Application Performance Modeling.
Proceedings of the 48th International Conference on Parallel Processing, 2019

Calibrating Sensing Drift in Tomographic Inversion.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Manifold Sampling for Optimization of Nonconvex Functions That Are Piecewise Linear Compositions of Smooth Components.
SIAM J. Optim., 2018

Asynchronously parallel optimization solver for finding multiple minima.
Math. Program. Comput., 2018

Machine Learning Based Parallel I/O Predictive Modeling: A Case Study on Lustre File Systems.
Proceedings of the High Performance Computing - 33rd International Conference, 2018

DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks.
Proceedings of the 25th IEEE International Conference on High Performance Computing, 2018

Modeling I/O Performance Variability Using Conditional Variational Autoencoders.
Proceedings of the IEEE International Conference on Cluster Computing, 2018

CONORBIT: constrained optimization by radial basis function interpolation in trust regions.
Optim. Methods Softw., 2017

Analysis and Correlation of Application I/O Performance and System-Wide I/O Activity.
Proceedings of the 2017 International Conference on Networking, Architecture, and Storage, 2017

Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales.
Proceedings of the Euro-Par 2017: Parallel Processing - 23rd International Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain, August 28, 2017

Understanding and Improving the Trust in Results of Numerical Simulations and Scientific Data Analytics.
Proceedings of the Euro-Par 2017: Parallel Processing Workshops, 2017

Technometrics, 2016

Modeling an Augmented Lagrangian for Blackbox Constrained Optimization.
Technometrics, 2016

Manifold Sampling for ℓ<sub>1</sub> Nonconvex Optimization.
SIAM J. Optim., 2016

Optimization-Based Approach for Joint X-Ray Fluorescence and Transmission Tomographic Inversion.
SIAM J. Imaging Sci., 2016

Doing Moore with Less - Leapfrogging Moore's Law with Inexactness for Supercomputing.
CoRR, 2016

AutoMOMML: Automatic Multi-objective Modeling with Machine Learning.
Proceedings of the High Performance Computing - 31st International Conference, 2016

Overcoming the power wall by exploiting inexactness and emerging COTS architectural features: Trading precision for improving application quality.
Proceedings of the 29th IEEE International System-on-Chip Conference, 2016

Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Exploiting Performance Portability in Search Algorithms for Autotuning.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

Management, analysis, and visualization of experimental and observational data - The convergence of data and computing.
Proceedings of the 12th IEEE International Conference on e-Science, 2016

ACCOLADES: A Scalable Workflow Framework for Large-Scale Simulation and Analyses of Automotive Engines.
Proceedings of the High Performance Computing - 30th International Conference, 2015

Visualizing and Improving the Robustness of Phase Retrieval Algorithms.
Proceedings of the International Conference on Computational Science, 2015

Autotuning FPGA Design Parameters for Performance and Power.
Proceedings of the 23rd IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2015

Collective I/O Tuning Using Analytical and Machine Learning Models.
Proceedings of the 2015 IEEE International Conference on Cluster Computing, 2015

Dynamic Model-Driven Parallel I/O Performance Tuning.
Proceedings of the 2015 IEEE International Conference on Cluster Computing, 2015

Do you trust derivatives or differences?
J. Comput. Phys., 2014

Analysis of the Tradeoffs Between Energy and Run Time for Multilevel Checkpointing.
Proceedings of the High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation, 2014

Improving parallel I/O autotuning with performance modeling.
Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing, 2014

Energy-performance tradeoffs in multilevel checkpoint strategies.
Proceedings of the 2014 IEEE International Conference on Cluster Computing, 2014

Global Convergence of Radial Basis Function Trust-Region Algorithms for Derivative-Free Optimization.
SIAM Rev., 2013

Non-intrusive termination of noisy optimization.
Optim. Methods Softw., 2013

Axially deformed solution of the Skyrme-Hartree-Fock-Bogoliubov equations using the transformed harmonic oscillator basis (II) hfbtho v2.00d: A new version of the program.
Comput. Phys. Commun., 2013

Computational nuclear quantum many-body problem: The UNEDF project.
Comput. Phys. Commun., 2013

Unsupervised cell identification on multidimensional X-ray fluorescence datasets.
Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference, 2013

Multi Objective Optimization of HPC Kernels for Performance, Power, and Energy.
Proceedings of the High Performance Computing Systems. Performance Modeling, Benchmarking and Simulation, 2013

Empirical performance modeling of GPU kernels using active learning.
Proceedings of the Parallel Computing: Accelerating Computational Science and Engineering (CSE), 2013

Active-learning-based surrogate models for empirical performance tuning.
Proceedings of the 2013 IEEE International Conference on Cluster Computing, 2013

Estimating Derivatives of Noisy Simulations.
ACM Trans. Math. Softw., 2012

SPAPT: Search Problems in Automatic Performance Tuning.
Proceedings of the International Conference on Computational Science, 2012

An Experimental Study of Global and Local Search Algorithms in Empirical Performance Tuning.
Proceedings of the High Performance Computing for Computational Science, 2012

Estimating Computational Noise.
SIAM J. Sci. Comput., 2011

Global Convergence of Radial Basis Function Trust Region Derivative-Free Algorithms.
SIAM J. Optim., 2011

Can search algorithms save large-scale automatic performance tuning?
Proceedings of the International Conference on Computational Science, 2011

Advancing Nuclear Physics Through TOPS Solvers and Tools
CoRR, 2011

Benchmarking Derivative-Free Optimization Algorithms.
SIAM J. Optim., 2009

ORBIT: Optimization by Radial Basis Function Interpolation in Trust-Regions.
SIAM J. Sci. Comput., 2008

Maximizing influence in a competitive social network: a follower's perspective.
Proceedings of the 9th International Conference on Electronic Commerce: The Wireless World of Electronic Commerce, 2007

Improving non-negative matrix factorizations through structured initialization.
Pattern Recognit., 2004