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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
11792018
Simple black-box adversarial attacks
C Guo, JR Gardner, Y You, AG Wilson, KQ Weinberger
International Conference on Machine Learning, 2019
5842019
Bayesian Optimization with Inequality Constraints.
JR Gardner, MJ Kusner, ZE Xu, KQ Weinberger, JP Cunningham
ICML 2014, 937-945, 2014
5502014
Scalable global optimization via local bayesian optimization
D Eriksson, M Pearce, JR Gardner, R Turner, M Poloczek
Advances in Neural Information Processing Systems, 2019
4572019
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
3582017
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
2652019
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
1192017
Constant-time predictive distributions for Gaussian processes
G Pleiss, JR Gardner, KQ Weinberger, AG Wilson
International Conference on Machine Learning, 2018
1152018
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
872015
Product kernel interpolation for scalable Gaussian processes
JR Gardner, G Pleiss, R Wu, KQ Weinberger, AG Wilson
Artificial Intelligence and Statistics, 2018
822018
Parametric Gaussian Process Regressors
M Jankowiak, G Pleiss, JR Gardner
International Conference on Machine Learning, 2020
772020
Adversarial prompting for black box foundation models
N Maus, P Chao, E Wong, J Gardner
arXiv preprint arXiv:2302.04237 1 (2), 2023
73*2023
Differentially private Bayesian optimization
M Kusner, J Gardner, R Garnett, K Weinberger
International conference on machine learning, 918-927, 2015
682015
Fast, continuous audiogram estimation using machine learning
XD Song, BM Wallace, JR Gardner, NM Ledbetter, KQ Weinberger, ...
Ear and hearing 36 (6), e326-e335, 2015
652015
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
602015
Learning performance-improving code edits
A Shypula, A Madaan, Y Zeng, U Alon, J Gardner, M Hashemi, G Neubig, ...
International Conference on Learning Representations, 2024
592024
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
552022
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
502015
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
482020
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
462020
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