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Jacob Gardner
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Gpytorch: Blackbox matrix-matrix gaussian process inference with gpu acceleration
JR Gardner, G Pleiss, D Bindel, KQ Weinberger, AG Wilson
Advances in Neural Information Processing Systems, 2018
9402018
Bayesian Optimization with Inequality Constraints.
JR Gardner, MJ Kusner, ZE Xu, KQ Weinberger, JP Cunningham
ICML 2014, 937-945, 2014
4662014
Simple black-box adversarial attacks
C Guo, JR Gardner, Y You, AG Wilson, KQ Weinberger
International Conference on Machine Learning, 2019
4642019
Scalable global optimization via local bayesian optimization
D Eriksson, M Pearce, JR Gardner, R Turner, M Poloczek
Advances in Neural Information Processing Systems, 2019
3292019
Deep feature interpolation for image content changes
P Upchurch*, J Gardner*, G Pleiss, R Pless, N Snavely, K Bala, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2017
3192017
Exact Gaussian processes on a million data points
KA Wang, G Pleiss, JR Gardner, S Tyree, KQ Weinberger, AG Wilson
Advances in Neural Information Processing Systems, 2019
2392019
Constant-time predictive distributions for Gaussian processes
G Pleiss, JR Gardner, KQ Weinberger, AG Wilson
International Conference on Machine Learning, 2018
1022018
Discovering and exploiting additive structure for Bayesian optimization
J Gardner, C Guo, K Weinberger, R Garnett, R Grosse
Artificial Intelligence and Statistics, 1311-1319, 2017
962017
Deep manifold traversal: Changing labels with convolutional features
JR Gardner, P Upchurch, MJ Kusner, Y Li, KQ Weinberger, K Bala, ...
arXiv preprint arXiv:1511.06421, 2015
832015
Product kernel interpolation for scalable Gaussian processes
JR Gardner, G Pleiss, R Wu, KQ Weinberger, AG Wilson
Artificial Intelligence and Statistics, 2018
712018
Parametric Gaussian Process Regressors
M Jankowiak, G Pleiss, JR Gardner
International Conference on Machine Learning, 2020
65*2020
Differentially private Bayesian optimization
M Kusner, J Gardner, R Garnett, K Weinberger
International conference on machine learning, 918-927, 2015
612015
A reduction of the elastic net to support vector machines with an application to GPU computing
Q Zhou, W Chen, S Song, J Gardner, K Weinberger, Y Chen
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
582015
Fast, continuous audiogram estimation using machine learning
XD Song, BM Wallace, JR Gardner, NM Ledbetter, KQ Weinberger, ...
Ear and hearing 36 (6), e326, 2015
512015
Bayesian active model selection with an application to automated audiometry
J Gardner, G Malkomes, R Garnett, KQ Weinberger, D Barbour, ...
Advances in neural information processing systems 28, 2015
462015
Fast matrix square roots with applications to Gaussian processes and Bayesian optimization
G Pleiss, M Jankowiak, D Eriksson, A Damle, JR Gardner
Advances in Neural Information Processing Systems, 2020
382020
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees
S Jiang, DR Jiang, M Balandat, B Karrer, JR Gardner, R Garnett
Advances in Neural Information Processing Systems, 2020
352020
Psychophysical detection testing with Bayesian active learning.
JR Gardner, X Song, KQ Weinberger, DL Barbour, JP Cunningham
UAI, 286-295, 2015
322015
Parallel support vector machines in practice
S Tyree, JR Gardner, KQ Weinberger, K Agrawal, J Tran
arXiv preprint arXiv:1404.1066, 2014
312014
Local Latent Space Bayesian Optimization over Structured Inputs
N Maus, HT Jones, JS Moore, MJ Kusner, J Bradshaw, JR Gardner
Advances in Neural Information Processing Systems, 2022
282022
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