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ORCIDDavid Eriksson
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2020 – today
- 2024
[i20]Natalie Maus, Kyurae Kim, Geoff Pleiss, David Eriksson, John P. Cunningham, Jacob R. Gardner:
Approximation-Aware Bayesian Optimization. CoRR abs/2406.04308 (2024)- [i19]Aryan Deshwal, Sait Cakmak, Yuhou Xia, David Eriksson:
Sample-Efficient Bayesian Optimization with Transfer Learning for Heterogeneous Search Spaces. CoRR abs/2409.05325 (2024) - [i18]Sebastian Ament, Elizabeth Santorella, David Eriksson, Ben Letham, Maximilian Balandat, Eytan Bakshy:
Robust Gaussian Processes via Relevance Pursuit. CoRR abs/2410.24222 (2024) - 2023
- [c16]Natalie Maus, Kaiwen Wu, David Eriksson, Jacob R. Gardner:
Discovering Many Diverse Solutions with Bayesian Optimization. AISTATS 2023: 1779-1798 - [c15]Sulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy:
Sparse Bayesian optimization. AISTATS 2023: 3754-3774 - [c14]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: 7021-7039 - [c13]Sebastian Ament, Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy:
Unexpected Improvements to Expected Improvement for Bayesian Optimization. NeurIPS 2023 - [i17]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 abs/2303.01774 (2023) - [i16]Sebastian Ament, Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy:
Unexpected Improvements to Expected Improvement for Bayesian Optimization. CoRR abs/2310.20708 (2023) - 2022
- [c12]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 - [c11]Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy:
Multi-objective Bayesian optimization over high-dimensional search spaces. UAI 2022: 507-517 - [i15]Sulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy:
Sparse Bayesian Optimization. CoRR abs/2203.01900 (2022) - [i14]Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A. Osborne, Eytan Bakshy:
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization. CoRR abs/2210.10199 (2022) - [i13]Natalie Maus, Kaiwen Wu, David Eriksson, Jacob R. Gardner:
Discovering Many Diverse Solutions with Bayesian Optimization. CoRR abs/2210.10953 (2022) - 2021
- [c10]David Eriksson, Matthias Poloczek:
Scalable Constrained Bayesian Optimization. AISTATS 2021: 730-738 - [c9]David Eriksson, Martin Jankowiak:
High-dimensional Bayesian optimization with sparse axis-aligned subspaces. UAI 2021: 493-503 - [c8]Eric Hans Lee, David Eriksson, Valerio Perrone, Matthias W. Seeger:
A Nonmyopic Approach to Cost-Constrained Bayesian Optimization. UAI 2021: 568-577 - [i12]David Eriksson, Martin Jankowiak:
High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces. CoRR abs/2103.00349 (2021) - [i11]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 abs/2104.10201 (2021) - [i10]Eric Hans Lee, David Eriksson, Valerio Perrone, Matthias W. Seeger:
A Nonmyopic Approach to Cost-Constrained Bayesian Optimization. CoRR abs/2106.06079 (2021) - [i9]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 abs/2106.11890 (2021) - [i8]Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy:
Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces. CoRR abs/2109.10964 (2021) - 2020
- [c7]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 - [c6]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: 3-26 - [c5]Eric Hans Lee, David Eriksson, David Bindel, Bolong Cheng, Mike Mccourt:
Efficient Rollout Strategies for Bayesian Optimization. UAI 2020: 260-269 - [i7]David Eriksson, Matthias Poloczek:
Scalable Constrained Bayesian Optimization. CoRR abs/2002.08526 (2020) - [i6]Eric Hans Lee, David Eriksson, Bolong Cheng, Michael McCourt, David Bindel:
Efficient Rollout Strategies for Bayesian Optimization. CoRR abs/2002.10539 (2020) - [i5]Geoff Pleiss, Martin Jankowiak, David Eriksson
, Anil Damle, Jacob R. Gardner:
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization. CoRR abs/2006.11267 (2020)
2010 – 2019
- 2019
- [c4]David Eriksson, Michael Pearce, Jacob R. Gardner, Ryan Turner, Matthias Poloczek:
Scalable Global Optimization via Local Bayesian Optimization. NeurIPS 2019: 5497-5508 - [i4]David Eriksson, David Bindel, Christine A. Shoemaker:
pySOT and POAP: An event-driven asynchronous framework for surrogate optimization. CoRR abs/1908.00420 (2019) - [i3]David Eriksson, Michael Pearce, Jacob R. Gardner, Ryan Turner, Matthias Poloczek:
Scalable Global Optimization via Local Bayesian Optimization. CoRR abs/1910.01739 (2019) - 2018
- [c3]David Eriksson, Kun Dong, Eric Hans Lee, David Bindel, Andrew Gordon Wilson:
Scaling Gaussian Process Regression with Derivatives. NeurIPS 2018: 6868-6878 - [i2]David Eriksson, Kun Dong, Eric Hans Lee, David Bindel, Andrew Gordon Wilson:
Scaling Gaussian Process Regression with Derivatives. CoRR abs/1810.12283 (2018) - 2017
- [j14]Cinzia Sansone, Per Hilletofth, David Eriksson:
Critical operations capabilities for competitive manufacturing: a systematic review. Ind. Manag. Data Syst. 117(5): 801-837 (2017) - [j13]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): 16-22 (2017) - [j12]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: 971-982 (2017) - [c2]Kun Dong, David Eriksson, Hannes Nickisch, David Bindel, Andrew Gordon Wilson:
Scalable Log Determinants for Gaussian Process Kernel Learning. NIPS 2017: 6327-6337 - [i1]Kun Dong, David Eriksson, Hannes Nickisch, David Bindel, Andrew Gordon Wilson:
Scalable Log Determinants for Gaussian Process Kernel Learning. CoRR abs/1711.03481 (2017) - 2016
- [j11]David Eriksson, Evan Shellshear:
Fast exact shortest distance queries for massive point clouds. Graph. Model. 84: 28-37 (2016) - 2014
- [c1]David Eriksson, Evan Shellshear:
Approximate Distance Queries for Path-planning in Massive Point Clouds. ICINCO (2) 2014: 20-28 - 2013
- [j10]David Eriksson, Per Hilletofth, Olli-Pekka Hilmola:
Creating value through wholesaler and retailer interface. Ind. Manag. Data Syst. 113(8): 1169-1188 (2013) - 2012
- [j9]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): 101-122 (2012) - [j8]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): 181-197 (2012) - 2011
- [j7]David Eriksson, Raul Vicente, Kerstin Erika Schmidt:
A Linear Model of Phase-Dependent Power Correlations in Neuronal Oscillations. Frontiers Comput. Neurosci. 5: 34 (2011) - 2010
- [j6]David Eriksson, Johan Rathsman, Oscar Stål:
2HDMC - two-Higgs-doublet model calculator. Comput. Phys. Commun. 181(1): 189-205 (2010) - [j5]David Eriksson, Johan Rathsman, Oscar Stål:
2HDMC - two-Higgs-doublet model calculator. Comput. Phys. Commun. 181(4): 833-834 (2010) - [j4]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): 985 (2010) - [j3]Per Hilletofth, David Eriksson:
Coordinating new product development with supply chain management. Ind. Manag. Data Syst. 111(2): 264-281 (2010)
2000 – 2009
- 2004
- [j2]David Eriksson:
Extracting and exposing predictive cortical columns for selective attention. Neurocomputing 58-60: 625-631 (2004) - 2003
- [j1]David Eriksson, Erik Fransén, Yuri Zilberter, Anders Lansner:
Effects of short-term synaptic plasticity in a local microcircuit on cell firing. Neurocomputing 52-54: 7-12 (2003)
Coauthor Index
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last updated on 2024-12-01 00:19 CET by the dblp team
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