David Eriksson

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 37

Top Topics

Global Optimization

Gaussian Process

Monte Carlo Sampling

Top Venues

Publications

Natalie Maus, Kyurae Kim, Geoff Pleiss, David Eriksson, John P. Cunningham, Jacob R. Gardner
Approximation-Aware Bayesian Optimization. CoRR (2024)
Sebastian Ament, Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy
Unexpected Improvements to Expected Improvement for Bayesian Optimization. NeurIPS (2023)
Aryan Deshwal, Sebastian Ament, Maximilian Balandat, Eytan Bakshy, Janardhan Rao Doppa, David Eriksson
Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings. AISTATS (2023)
Sebastian Ament, Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy
Unexpected Improvements to Expected Improvement for Bayesian Optimization. CoRR (2023)
Sulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy
Sparse Bayesian optimization. AISTATS (2023)
Natalie Maus, Kaiwen Wu, David Eriksson, Jacob R. Gardner
Discovering Many Diverse Solutions with Bayesian Optimization. AISTATS (2023)
Aryan Deshwal, Sebastian Ament, Maximilian Balandat, Eytan Bakshy, Janardhan Rao Doppa, David Eriksson
Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings. CoRR (2023)
Sulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy
Sparse Bayesian Optimization. CoRR (2022)
Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy
Multi-objective Bayesian optimization over high-dimensional search spaces. UAI (2022)
Natalie Maus, Kaiwen Wu, David Eriksson, Jacob R. Gardner
Discovering Many Diverse Solutions with Bayesian Optimization. CoRR (2022)
Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A. Osborne, Eytan Bakshy
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization. NeurIPS (2022)
Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A. Osborne, Eytan Bakshy
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization. CoRR (2022)
Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy
Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces. CoRR (2021)
David Eriksson, Matthias Poloczek
Scalable Constrained Bayesian Optimization. AISTATS (2021)
David Eriksson, Martin Jankowiak
High-dimensional Bayesian optimization with sparse axis-aligned subspaces. UAI (2021)
David Eriksson, Pierce I-Jen Chuang, Samuel Daulton, Peng Xia, Akshat Shrivastava, Arun Babu, Shicong Zhao, Ahmed Aly, Ganesh Venkatesh, Maximilian Balandat
Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization. CoRR (2021)
Ryan Turner, David Eriksson, Michael McCourt, Juha Kiili, Eero Laaksonen, Zhen Xu, Isabelle Guyon
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020. CoRR (2021)
Eric Hans Lee, David Eriksson, Valerio Perrone, Matthias W. Seeger
A Nonmyopic Approach to Cost-Constrained Bayesian Optimization. CoRR (2021)
David Eriksson, Martin Jankowiak
High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces. CoRR (2021)
Eric Hans Lee, David Eriksson, Valerio Perrone, Matthias W. Seeger
A Nonmyopic Approach to Cost-Constrained Bayesian Optimization. UAI (2021)
Ryan Turner, David Eriksson, Michael McCourt, Juha Kiili, Eero Laaksonen, Zhen Xu, Isabelle Guyon
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020. NeurIPS (Competition and Demos) (2020)
Eric Hans Lee, David Eriksson, Bolong Cheng, Michael McCourt, David Bindel
Efficient Rollout Strategies for Bayesian Optimization. CoRR (2020)
Geoff Pleiss, Martin Jankowiak, David Eriksson, Anil Damle, Jacob R. Gardner
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization. CoRR (2020)
Geoff Pleiss, Martin Jankowiak, David Eriksson, Anil Damle, Jacob R. Gardner
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization. NeurIPS (2020)
David Eriksson, Matthias Poloczek
Scalable Constrained Bayesian Optimization. CoRR (2020)
Eric Hans Lee, David Eriksson, David Bindel, Bolong Cheng, Mike Mccourt
Efficient Rollout Strategies for Bayesian Optimization. UAI (2020)
David Eriksson, David Bindel, Christine A. Shoemaker
pySOT and POAP: An event-driven asynchronous framework for surrogate optimization. CoRR (2019)
David Eriksson, Michael Pearce, Jacob R. Gardner, Ryan Turner, Matthias Poloczek
Scalable Global Optimization via Local Bayesian Optimization. CoRR (2019)
David Eriksson, Michael Pearce, Jacob R. Gardner, Ryan Turner, Matthias Poloczek
Scalable Global Optimization via Local Bayesian Optimization. NeurIPS (2019)
David Eriksson, Kun Dong, Eric Hans Lee, David Bindel, Andrew Gordon Wilson
Scaling Gaussian Process Regression with Derivatives. CoRR (2018)
David Eriksson, Kun Dong, Eric Hans Lee, David Bindel, Andrew Gordon Wilson
Scaling Gaussian Process Regression with Derivatives. NeurIPS (2018)
Kun Dong, David Eriksson, Hannes Nickisch, David Bindel, Andrew Gordon Wilson
Scalable Log Determinants for Gaussian Process Kernel Learning. NIPS (2017)
Cinzia Sansone, Per Hilletofth, David Eriksson
Critical operations capabilities for competitive manufacturing: a systematic review. Ind. Manag. Data Syst. 117 (5) (2017)
Kun Dong, David Eriksson, Hannes Nickisch, David Bindel, Andrew Gordon Wilson
Scalable Log Determinants for Gaussian Process Kernel Learning. CoRR (2017)
Tiago Siebert Altavini, Sergio Andres Conde-Ocazionez, David Eriksson, Thomas Wunderle, Kerstin Erika Schmidt
Selective interhemispheric circuits account for a cardinal bias in spontaneous activity within early visual areas. NeuroImage 146 (2017)
Andreas Hoglund, Xingqin Lin, Olof Liberg, Ali Behravan, Emre A. Yavuz, Martin Van Der Zee, Yutao Sui, Tuomas Tirronen, Antti Ratilainen, David Eriksson
Overview of 3GPP Release 14 Enhanced NB-IoT. IEEE Netw. 31 (6) (2017)
David Eriksson, Evan Shellshear
Fast exact shortest distance queries for massive point clouds. Graph. Model. 84 (2016)
David Eriksson, Evan Shellshear
Approximate Distance Queries for Path-planning in Massive Point Clouds. ICINCO (2) (2014)
David Eriksson, Per Hilletofth, Olli-Pekka Hilmola
Creating value through wholesaler and retailer interface. Ind. Manag. Data Syst. 113 (8) (2013)
Per Hilletofth, David Eriksson, Olli-Pekka Hilmola
Two sides of a token: coordinating demand and supply at furniture wholesaler. Int. J. Manuf. Res. 7 (2) (2012)
David Eriksson, Carl Philip T. Hedenstierna
Matching supply chain strategy with business strategy and the results of a mismatch. Int. J. Manuf. Res. 7 (2) (2012)
David Eriksson, Raul Vicente, Kerstin Erika Schmidt
A Linear Model of Phase-Dependent Power Correlations in Neuronal Oscillations. Frontiers Comput. Neurosci. 5 (2011)
David Eriksson, Johan Rathsman, Oscar Stål
Erratum for "2HDMC - two-Higgs-doublet model calculator" [Comput. Phys. Commun. 181 (2010) 189]. Comput. Phys. Commun. 181 (5) (2010)
David Eriksson, Johan Rathsman, Oscar Stål
2HDMC - two-Higgs-doublet model calculator. Comput. Phys. Commun. 181 (4) (2010)
David Eriksson, Johan Rathsman, Oscar Stål
2HDMC - two-Higgs-doublet model calculator. Comput. Phys. Commun. 181 (1) (2010)
Per Hilletofth, David Eriksson
Coordinating new product development with supply chain management. Ind. Manag. Data Syst. 111 (2) (2010)
David Eriksson
Extracting and exposing predictive cortical columns for selective attention. Neurocomputing (2004)
David Eriksson, Erik Fransén, Yuri Zilberter, Anders Lansner
Effects of short-term synaptic plasticity in a local microcircuit on cell firing. Neurocomputing (2003)