Michael McCourt

According to our database, Michael McCourt authored at least 21 papers between 2013 and 2022.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2022

Bridging Offline and Online Experimentation: Constraint Active Search for Deployed Performance Optimization.

Junpei Komiyama, Gustavo Malkomes, Bolong Cheng, Michael McCourt

Trans. Mach. Learn. Res., 2022

Achieving Diversity in Objective Space for Sample-Efficient Search of Multiobjective Optimization Problems.

Eric Hans Lee, Bolong Cheng, Michael McCourt

Proceedings of the Winter Simulation Conference, 2022

2021

Bayesian optimization with approximate set kernels.

Jungtaek Kim, Michael McCourt, Tackgeun You, Saehoon Kim, Seungjin Choi

Mach. Learn., 2021

Beyond the Pareto Efficient Frontier: Constraint Active Search for Multiobjective Experimental Design.

Gustavo Malkomes, Bolong Cheng, Eric Hans Lee, Mike Mccourt

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

On variable and random shape Gaussian interpolations.

Sung Nok Chiu, Leevan Ling, Michael McCourt

Appl. Math. Comput., 2020

Efficient Rollout Strategies for Bayesian Optimization.

Eric Hans Lee, David Eriksson, David Bindel, Bolong Cheng, Mike Mccourt

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020.

Ryan Turner, David Eriksson, Michael McCourt, Juha Kiili, Eero Laaksonen, Zhen Xu, Isabelle Guyon

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

2019

Sampling Humans for Optimizing Preferences in Coloring Artwork.

Michael McCourt, Ian Dewancker

CoRR, 2019

Bayesian Optimization over Sets.

Jungtaek Kim, Michael McCourt, Tackgeun You, Saehoon Kim, Seungjin Choi

CoRR, 2019

2018

Orchestrate: Infrastructure for Enabling Parallelism during Hyperparameter Optimization.

Alexandra Johnson, Michael McCourt

CoRR, 2018

Sequential Preference-Based Optimization.

Ian Dewancker, Jakob Bauer, Michael McCourt

CoRR, 2018

Practical Bayesian optimization in the presence of outliers.

Ruben Martinez-Cantin, Kevin Tee, Michael McCourt

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Active Preference Learning for Personalized Portfolio Construction.

Kevin Tee, Michael McCourt, Ruben Martinez-Cantin, Ian Dewancker, Frank Liu

CoRR, 2017

Robust Bayesian Optimization with Student-t Likelihood.

Ruben Martinez-Cantin, Michael McCourt, Kevin Tee

CoRR, 2017

2016

Preemptive Termination of Suggestions during Sequential Kriging Optimization of a Brain Activity Reconstruction Simulation.

Michael McCourt, Ian Dewancker, Salvatore Ganci

CoRR, 2016

Evaluation System for a Bayesian Optimization Service.

Ian Dewancker, Michael McCourt, Scott Clark, Patrick Hayes, Alexandra Johnson, George Ke

CoRR, 2016

A Stratified Analysis of Bayesian Optimization Methods.

Ian Dewancker, Michael McCourt, Scott Clark, Patrick Hayes, Alexandra Johnson, George Ke

CoRR, 2016

Bayesian Optimization for Machine Learning : A Practical Guidebook.

Ian Dewancker, Michael McCourt, Scott Clark

CoRR, 2016

A Strategy for Ranking Optimization Methods using Multiple Criteria.

Ian Dewancker, Michael McCourt, Scott Clark, Patrick Hayes, Alexandra Johnson, George Ke

Proceedings of the 2016 Workshop on Automatic Machine Learning, 2016

2015

Sparse Matrix-Matrix Products Executed Through Coloring.

Michael McCourt, Barry Smith, Hong Zhang

SIAM J. Matrix Anal. Appl., 2015

2013

Multiphysics simulations: Challenges and opportunities.

David E. Keyes, Lois C. McInnes, Carol S. Woodward, William Gropp, Eric Myra, Michael Pernice, John B. Bell, Jed Brown, Alain Clo, Jeffrey M. Connors, Emil M. Constantinescu, Donald J. Estep, Kate Evans, Charbel Farhat, Ammar Hakim, Glenn Hammond, Glen Hansen, Judith Hill, Tobin Isaac, Xiangmin Jiao, Kirk E. Jordan, Dinesh K. Kaushik, Efthimios Kaxiras, Alice E. Koniges, Kihwan Lee, Aaron Lott, Qiming Lu, John Magerlein, Reed Maxwell, Michael McCourt, Miriam Mehl, Roger P. Pawlowski, Amanda Peters Randles, Daniel R. Reynolds, Beatrice Riviere, Ulrich Rüde, Timothy D. Scheibe, John N. Shadid, Brendan Sheehan, Mark S. Shephard, Andrew R. Siegel, Barry Smith, Xianzhu Tang, Cian Wilson, Barbara I. Wohlmuth

Int. J. High Perform. Comput. Appl., 2013