Следене
Jacob Gardner
Заглавие
Позовавания
Позовавания
Година
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
13732018
Simple black-box adversarial attacks
C Guo, JR Gardner, Y You, AG Wilson, KQ Weinberger
International Conference on Machine Learning, 2019
6592019
Bayesian Optimization with Inequality Constraints.
JR Gardner, MJ Kusner, ZE Xu, KQ Weinberger, JP Cunningham
ICML 2014, 937-945, 2014
6162014
Scalable global optimization via local bayesian optimization
D Eriksson, M Pearce, JR Gardner, R Turner, M Poloczek
Advances in Neural Information Processing Systems, 2019
5432019
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
3722017
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
2862019
Constant-time predictive distributions for Gaussian processes
G Pleiss, JR Gardner, KQ Weinberger, AG Wilson
International Conference on Machine Learning, 2018
1302018
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
1272017
Adversarial prompting for black box foundation models
N Maus, P Chao, E Wong, J Gardner
arXiv preprint arXiv:2302.04237 1 (2), 2023
95*2023
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
902015
Parametric Gaussian Process Regressors
M Jankowiak, G Pleiss, JR Gardner
International Conference on Machine Learning, 2020
892020
Product kernel interpolation for scalable Gaussian processes
JR Gardner, G Pleiss, R Wu, KQ Weinberger, AG Wilson
Artificial Intelligence and Statistics, 2018
892018
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
842024
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
722022
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
722015
Differentially private Bayesian optimization
M Kusner, J Gardner, R Garnett, K Weinberger
International conference on machine learning, 918-927, 2015
682015
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
632015
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
572020
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
552020
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
542015
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