Stefan M. Wild

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 69

Top Topics

Optimization Methods

Constrained Optimization

Top Venues

Publications

Moses Y.-H. Chan, Matthew Plumlee, Stefan M. Wild
Constructing a Simulation Surrogate with Partially Observed Output. Technometrics 66 (1) (2024)
Stefan M. Wild
Research Spotlights. SIAM Rev. 66 (1) (2024)
Özge Sürer, Matthew Plumlee, Stefan M. Wild
Sequential Bayesian Experimental Design for Calibration of Expensive Simulation Models. Technometrics 66 (2) (2024)
Stefan M. Wild
Research Spotlights. SIAM Rev. 66 (2) (2024)
Stefan M. Wild
Research Spotlights. SIAM Rev. 66 (3) (2024)
K. J. Dzahini, Stefan M. Wild
Stochastic Trust-Region Algorithm in Random Subspaces with Convergence and Expected Complexity Analyses. SIAM J. Optim. 34 (3) (2024)
Stephen Hudson, Jeffrey Larson, John-Luke Navarro, Stefan M. Wild
Portable, heterogeneous ensemble workflows at scale using libEnsemble. CoRR (2024)
Matt Menickelly, Stefan M. Wild
Stochastic average model methods. Comput. Optim. Appl. 88 (2) (2024)
Abdulkadir Canatar, Evan Peters, Cengiz Pehlevan, Stefan M. Wild, Ruslan Shaydulin
Bandwidth Enables Generalization in Quantum Kernel Models. Trans. Mach. Learn. Res. 2023 (2023)
Stefan M. Wild
Research Spotlights. SIAM Rev. 65 (4) (2023)
Stefan M. Wild
Research Spotlights. SIAM Rev. 65 (1) (2023)
Jeffrey Larson, Misha Padidar, Stefan M. Wild
Modeling approaches for addressing unrelaxable bound constraints with unconstrained optimization methods. Optim. Lett. 17 (3) (2023)
Tyler H. Chang, Stefan M. Wild
Designing a Framework for Solving Multiobjective Simulation Optimization Problems. CoRR (2023)
Raghu Bollapragada, Stefan M. Wild
Adaptive sampling quasi-Newton methods for zeroth-order stochastic optimization. Math. Program. Comput. 15 (2) (2023)
Aleksandra Ciprijanovic, A. Lewis, K. Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection. CoRR (2023)
Stefan M. Wild
Research Spotlights. SIAM Rev. 65 (3) (2023)
Tyler H. Chang, Stefan M. Wild
ParMOO: A Python library for parallel multiobjective simulation optimization. J. Open Source Softw. 8 (82) (2023)
Stefan M. Wild
Research Spotlights. SIAM Rev. 65 (2) (2023)
Tyler H. Chang, Jakob R. Elias, Stefan M. Wild, Santanu Chaudhuri, Joseph A. Libera
A framework for fully autonomous design of materials via multiobjective optimization and active learning: challenges and next steps. CoRR (2023)
Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild
DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection. Mach. Learn. Sci. Technol. 4 (2) (2023)
Ishan Abhinit, Emily K. Adams, Khairul Alam, Brian Chase, Ewa Deelman, Lev Gorenstein, Stephen Hudson, Tanzima Z. Islam, Jeffrey Larson, Geoffrey Lentner, Anirban Mandal, John-Luke Navarro, Bogdan Nicolae, Line Pouchard, Robert B. Ross, Banani Roy, Mats Rynge, Alexander Serebrenik, Karan Vahi, Stefan M. Wild, Yufeng Xin, Rafael Ferreira da Silva, Rosa Filgueira
Novel Proposals for FAIR, Automated, Recommendable, and Robust Workflows. WORKS@SC (2022)
Stephen Hudson, Jeffrey Larson, John-Luke Navarro, Stefan M. Wild
libEnsemble: A Library to Coordinate the Concurrent Evaluation of Dynamic Ensembles of Calculations. IEEE Trans. Parallel Distributed Syst. 33 (4) (2022)
Aleksandra Ciprijanovic, Diana Kafkes, Gregory F. Snyder, F. Javier Sánchez, Gabriel Nathan Perdue, Kevin Pedro, Brian Nord, Sandeep Madireddy, Stefan M. Wild
DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification. Mach. Learn. Sci. Technol. 3 (3) (2022)
Abdulkadir Canatar, Evan Peters, Cengiz Pehlevan, Stefan M. Wild, Ruslan Shaydulin
Bandwidth Enables Generalization in Quantum Kernel Models. CoRR (2022)
Lucas Slattery, Ruslan Shaydulin, Shouvanik Chakrabarti, Marco Pistoia, Sami Khairy, Stefan M. Wild
Numerical evidence against advantage with quantum fidelity kernels on classical data. CoRR (2022)
Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild
Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection. CoRR (2022)
Jeffrey Larson, Sven Leyffer, Prashant Palkar, Stefan M. Wild
A method for convex black-box integer global optimization. J. Glob. Optim. 80 (2) (2021)
Arindam Fadikar, Stefan M. Wild, Jonas Chaves-Montero
Scalable Statistical Inference of Photometric Redshift via Data Subsampling. CoRR (2021)
Jed Brown, Yunhui He, Scott MacLachlan, Matt Menickelly, Stefan M. Wild
Tuning Multigrid Methods with Robust Optimization and Local Fourier Analysis. SIAM J. Sci. Comput. 43 (1) (2021)
Aleksandra Ciprijanovic, Diana Kafkes, Gregory F. Snyder, F. Javier Sánchez, Gabriel Nathan Perdue, Kevin Pedro, Brian Nord, Sandeep Madireddy, Stefan M. Wild
DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification. CoRR (2021)
Nathan Wycoff, Mickaël Binois, Stefan M. Wild
Sequential Learning of Active Subspaces. J. Comput. Graph. Stat. 30 (4) (2021)
Aleksandra Ciprijanovic, Diana Kafkes, Gabriel N. Perdue, Kevin Pedro, Gregory F. Snyder, F. Javier Sánchez, Sandeep Madireddy, Stefan M. Wild, Brian Nord
Robustness of deep learning algorithms in astronomy - galaxy morphology studies. CoRR (2021)
Stephen Hudson, Jeffrey Larson, John-Luke Navarro, Stefan M. Wild
libEnsemble: A Library to Coordinate the Concurrent Evaluation of Dynamic Ensembles of Calculations. CoRR (2021)
Aydin Buluç, Tamara G. Kolda, Stefan M. Wild, Mihai Anitescu, Anthony DeGennaro, John Jakeman, Chandrika Kamath, Ramakrishnan Kannan, Miles E. Lopes, Per-Gunnar Martinsson, Kary Myers, Jelani Nelson, Juan M. Restrepo, C. Seshadhri, Draguna L. Vrabie, Brendt Wohlberg, Stephen J. Wright, Chao Yang, Peter Zwart
Randomized Algorithms for Scientific Computing (RASC). CoRR (2021)
Henri Casanova, Ewa Deelman, Sandra Gesing, Michael D. Hildreth, Stephen Hudson, William Koch, Jeffrey Larson, Mary Ann McDowell, Natalie Meyers, John-Luke Navarro, George Papadimitriou, Ryan Tanaka, Ian J. Taylor, Douglas Thain, Stefan M. Wild, Rosa Filgueira, Rafael Ferreira da Silva
Emerging Frameworks for Advancing Scientific Workflows Research, Development, and Education. WORKS (2021)
Ruslan Shaydulin, Stefan M. Wild
Importance of Kernel Bandwidth in Quantum Machine Learning. CoRR (2021)
Arindam Fadikar, Stefan M. Wild, Jonas Chaves-Montero
Scalable Statistical Inference of Photometric Redshift via Data Subsampling. ICCS (5) (2021)
Zichao (Wendy) Di, Esteban Rangel, Shinjae Yoo, Stefan M. Wild
Hierarchical Analysis of Halo Center in Cosmology. ICCS (1) (2021)
Raghu Bollapragada, Stefan M. Wild
Adaptive Sampling Quasi-Newton Methods for Zeroth-Order Stochastic Optimization. CoRR (2021)
Sven Leyffer, Matt Menickelly, Todd S. Munson, Charlie Vanaret, Stefan M. Wild
A survey of nonlinear robust optimization. INFOR Inf. Syst. Oper. Res. 58 (2) (2020)
Jed Brown, Yunhui He, Scott MacLachlan, Matt Menickelly, Stefan M. Wild
Tuning Multigrid Methods with Robust Optimization. CoRR (2020)
Matt Menickelly, Stefan M. Wild
Derivative-free robust optimization by outer approximations. Math. Program. 179 (1) (2020)
Nathanaël Cheriere, Matthieu Dorier, Gabriel Antoniu, Stefan M. Wild, Sven Leyffer, Robert B. Ross
Pufferscale: Rescaling HPC Data Services for High Energy Physics Applications. CCGRID (2020)
Anthony P. Austin, Zichao Wendy Di, Sven Leyffer, Stefan M. Wild
Simultaneous Sensing Error Recovery and Tomographic Inversion Using an Optimization-Based Approach. SIAM J. Sci. Comput. 41 (3) (2019)
Jeffrey Larson, Matt Menickelly, Stefan M. Wild
Derivative-free optimization methods. Acta Numer. 28 (2019)
Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan M. Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens
Scalable reinforcement-learning-based neural architecture search for cancer deep learning research. SC (2019)
Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan M. Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens
Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research. CoRR (2019)
Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Glenn K. Lockwood, Robert B. Ross, Shane Snyder, Stefan M. Wild
Adaptive Learning for Concept Drift in Application Performance Modeling. ICPP (2019)
Nathan Wycoff, Mickaël Binois, Stefan M. Wild
Sequential Learning of Active Subspaces. CoRR (2019)
Xiang Huang, Stefan M. Wild, Zichao Wendy Di
Calibrating Sensing Drift in Tomographic Inversion. ICIP (2019)
Kamil A. Khan, Jeffrey Larson, Stefan M. Wild
Manifold Sampling for Optimization of Nonconvex Functions That Are Piecewise Linear Compositions of Smooth Components. SIAM J. Optim. 28 (4) (2018)
Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Robert B. Ross, Shane Snyder, Stefan M. Wild
Machine Learning Based Parallel I/O Predictive Modeling: A Case Study on Lustre File Systems. ISC (2018)
Jeffrey Larson, Stefan M. Wild
Asynchronously parallel optimization solver for finding multiple minima. Math. Program. Comput. 10 (3) (2018)
Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Robert B. Ross, Shane Snyder, Stefan M. Wild
Modeling I/O Performance Variability Using Conditional Variational Autoencoders. CLUSTER (2018)
Prasanna Balaprakash, Michael Salim, Thomas D. Uram, Venkat Vishwanath, Stefan M. Wild
DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks. HiPC (2018)
Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Robert B. Ross, Shane Snyder, Stefan M. Wild
Analysis and Correlation of Application I/O Performance and System-Wide I/O Activity. NAS (2017)
Franck Cappello, Rinku Gupta, Sheng Di, Emil M. Constantinescu, Thomas Peterka, Stefan M. Wild
Understanding and Improving the Trust in Results of Numerical Simulations and Scientific Data Analytics. Euro-Par Workshops (2017)
Ian T. Foster, Mark Ainsworth, Bryce Allen, Julie Bessac, Franck Cappello, Jong Youl Choi, Emil M. Constantinescu, Philip E. Davis, Sheng Di, Zichao Wendy Di, Hanqi Guo, Scott Klasky, Kerstin Kleese van Dam, Tahsin M. Kurç, Qing Liu, Abid Malik, Kshitij Mehta, Klaus Mueller, Todd S. Munson, George Ostrouchov, Manish Parashar, Tom Peterka, Line Pouchard, Dingwen Tao, Ozan Tugluk, Stefan M. Wild, Matthew Wolf, Justin M. Wozniak, Wei Xu, Shinjae Yoo
Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales. Euro-Par (2017)
Rommel G. Regis, Stefan M. Wild
CONORBIT: constrained optimization by radial basis function interpolation in trust regions. Optim. Methods Softw. 32 (3) (2017)
Mike Fagan, Jeremy Schlachter, Kazutomo Yoshii, Sven Leyffer, Krishna V. Palem, Marc Snir, Stefan M. Wild, Christian C. Enz
Overcoming the power wall by exploiting inexactness and emerging COTS architectural features: Trading precision for improving application quality. SoCC (2016)
Victor Picheny, Robert B. Gramacy, Stefan M. Wild, Sébastien Le Digabel
Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian. NIPS (2016)
Amit Roy, Prasanna Balaprakash, Paul D. Hovland, Stefan M. Wild
Exploiting Performance Portability in Search Algorithms for Autotuning. IPDPS Workshops (2016)
Prasanna Balaprakash, Ananta Tiwari, Stefan M. Wild, Laura Carrington, Paul D. Hovland
AutoMOMML: Automatic Multi-objective Modeling with Machine Learning. ISC (2016)
Robert B. Gramacy, Genetha A. Gray, Sébastien Le Digabel, Herbert K. H. Lee, Pritam Ranjan, Garth N. Wells, Stefan M. Wild
Modeling an Augmented Lagrangian for Blackbox Constrained Optimization. Technometrics 58 (1) (2016)
Zichao (Wendy) Di, Sven Leyffer, Stefan M. Wild
Optimization-Based Approach for Joint X-Ray Fluorescence and Transmission Tomographic Inversion. SIAM J. Imaging Sci. 9 (1) (2016)
E. Wes Bethel, Martin Greenwald, Kerstin Kleese van Dam, Manish Parashar, Stefan M. Wild, H. Steven Wiley
Management, analysis, and visualization of experimental and observational data - The convergence of data and computing. eScience (2016)
Sven Leyffer, Stefan M. Wild, Mike Fagan, Marc Snir, Krishna V. Palem, Kazutomo Yoshii, Hal Finkel
Doing Moore with Less - Leapfrogging Moore's Law with Inexactness for Supercomputing. CoRR (2016)
Robert B. Gramacy, Genetha A. Gray, Sébastien Le Digabel, Herbert K. H. Lee, Pritam Ranjan, Garth N. Wells, Stefan M. Wild
Rejoinder. Technometrics 58 (1) (2016)
Jeffrey Larson, Matt Menickelly, Stefan M. Wild
Nonconvex Optimization. SIAM J. Optim. 26 (4) (2016)
Shashi M. Aithal, Stefan M. Wild
ACCOLADES: A Scalable Workflow Framework for Large-Scale Simulation and Analyses of Automotive Engines. ISC (2015)
Ashish Tripathi, Sven Leyffer, Todd S. Munson, Stefan M. Wild
Visualizing and Improving the Robustness of Phase Retrieval Algorithms. ICCS (2015)
Azamat Mametjanov, Prasanna Balaprakash, Chekuri Choudary, Paul D. Hovland, Stefan M. Wild, Gerald Sabin
Autotuning FPGA Design Parameters for Performance and Power. FCCM (2015)
Florin Isaila, Prasanna Balaprakash, Stefan M. Wild, Dries Kimpe, Robert Latham, Robert B. Ross, Paul D. Hovland
Collective I/O Tuning Using Analytical and Machine Learning Models. CLUSTER (2015)
Babak Behzad, Surendra Byna, Stefan M. Wild, Prabhat, Marc Snir
Dynamic Model-Driven Parallel I/O Performance Tuning. CLUSTER (2015)
Jorge J. Moré, Stefan M. Wild
Do you trust derivatives or differences? J. Comput. Phys. 273 (2014)
Leonardo Arturo Bautista-Gomez, Prasanna Balaprakash, Mohamed-Slim Bouguerra, Stefan M. Wild, Franck Cappello, Paul D. Hovland
Energy-performance tradeoffs in multilevel checkpoint strategies. CLUSTER (2014)
Babak Behzad, Surendra Byna, Stefan M. Wild, Prabhat, Marc Snir
Improving parallel I/O autotuning with performance modeling. HPDC (2014)
Prasanna Balaprakash, Leonardo Arturo Bautista-Gomez, Mohamed-Slim Bouguerra, Stefan M. Wild, Franck Cappello, Paul D. Hovland
Analysis of the Tradeoffs Between Energy and Run Time for Multilevel Checkpointing. PMBS@SC (2014)
Siwei Wang, Jesse Ward, Sven Leyffer, Stefan M. Wild, Chris Jacobsen, Stefan Vogt
Unsupervised cell identification on multidimensional X-ray fluorescence datasets. SIGGRAPH Posters (2013)
Prasanna Balaprakash, Ananta Tiwari, Stefan M. Wild
Multi Objective Optimization of HPC Kernels for Performance, Power, and Energy. PMBS@SC (2013)
Prasanna Balaprakash, Karl Rupp, Azamat Mametjanov, Robert B. Gramacy, Paul D. Hovland, Stefan M. Wild
Empirical performance modeling of GPU kernels using active learning. PARCO (2013)
Scott Bogner, Aurel Bulgac, Joseph A. Carlson, Jonathan Engel, George L. Fann, Richard J. Furnstahl, Stefano Gandolfi, Gaute Hagen, Mihai Horoi, Calvin W. Johnson, Markus Kortelainen, Ewing L. Lusk, Pieter Maris, Hai Ah Nam, Petr Navratil, Witold Nazarewicz, Esmond G. Ng, Gustavo P. A. Nobre, W. Erich Ormand, Thomas Papenbrock, Junchen Pei, Steven C. Pieper, Sofia Quaglioni, Kenneth J. Roche, Jason Sarich, Nicolas Schunck, Masha Sosonkina, Jun Terasaki, Ian J. Thompson, James P. Vary, Stefan M. Wild
Computational nuclear quantum many-body problem: The UNEDF project. Comput. Phys. Commun. 184 (10) (2013)
Jeffrey Larson, Stefan M. Wild
Non-intrusive termination of noisy optimization. Optim. Methods Softw. 28 (5) (2013)
M. V. Stoitsov, Nicolas Schunck, Markus Kortelainen, N. Michel, H. Nam, E. Olsen, Jason Sarich, Stefan M. Wild
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. 184 (6) (2013)
Prasanna Balaprakash, Robert B. Gramacy, Stefan M. Wild
Active-learning-based surrogate models for empirical performance tuning. CLUSTER (2013)
Stefan M. Wild, Christine A. Shoemaker
Global Convergence of Radial Basis Function Trust-Region Algorithms for Derivative-Free Optimization. SIAM Rev. 55 (2) (2013)
Prasanna Balaprakash, Stefan M. Wild, Boyana Norris
SPAPT: Search Problems in Automatic Performance Tuning. ICCS (2012)
Jorge J. Moré, Stefan M. Wild
Estimating Derivatives of Noisy Simulations. ACM Trans. Math. Softw. 38 (3) (2012)
Prasanna Balaprakash, Stefan M. Wild, Paul D. Hovland
An Experimental Study of Global and Local Search Algorithms in Empirical Performance Tuning. VECPAR (2012)
Prasanna Balaprakash, Stefan M. Wild, Paul D. Hovland
Can search algorithms save large-scale automatic performance tuning? ICCS (2011)
Stefan M. Wild, Christine A. Shoemaker
Global Convergence of Radial Basis Function Trust Region Derivative-Free Algorithms. SIAM J. Optim. 21 (3) (2011)
Esmond G. Ng, Jason Sarich, Stefan M. Wild, Todd S. Munson, Hasan Metin Aktulga, Chao Yang, Pieter Maris, James P. Vary, Nicolas Schunck, M. G. Bertolli, Markus Kortelainen, Witold Nazarewicz, Thomas Papenbrock, M. V. Stoitsov
Advancing Nuclear Physics Through TOPS Solvers and Tools CoRR (2011)
Jorge J. Moré, Stefan M. Wild
Estimating Computational Noise. SIAM J. Sci. Comput. 33 (3) (2011)
Jorge J. Moré, Stefan M. Wild
Benchmarking Derivative-Free Optimization Algorithms. SIAM J. Optim. 20 (1) (2009)
Stefan M. Wild, Rommel G. Regis, Christine A. Shoemaker
ORBIT: Optimization by Radial Basis Function Interpolation in Trust-Regions. SIAM J. Sci. Comput. 30 (6) (2008)
Tim Carnes, Chandrashekhar Nagarajan, Stefan M. Wild, Anke van Zuylen
Maximizing influence in a competitive social network: a follower's perspective. ICEC (2007)
Stefan M. Wild, James Curry, Anne Dougherty
Improving non-negative matrix factorizations through structured initialization. Pattern Recognit. 37 (11) (2004)