Seuraa
Jacob Gardner
Nimike
Viittaukset
Viittaukset
Vuosi
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
13602018
Simple black-box adversarial attacks
C Guo, JR Gardner, Y You, AG Wilson, KQ Weinberger
International Conference on Machine Learning, 2019
6542019
Bayesian Optimization with Inequality Constraints.
JR Gardner, MJ Kusner, ZE Xu, KQ Weinberger, JP Cunningham
ICML 2014, 937-945, 2014
6072014
Scalable global optimization via local bayesian optimization
D Eriksson, M Pearce, JR Gardner, R Turner, M Poloczek
Advances in Neural Information Processing Systems, 2019
5422019
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
3712017
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
2832019
Constant-time predictive distributions for Gaussian processes
G Pleiss, JR Gardner, KQ Weinberger, AG Wilson
International Conference on Machine Learning, 2018
1292018
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
Product kernel interpolation for scalable Gaussian processes
JR Gardner, G Pleiss, R Wu, KQ Weinberger, AG Wilson
Artificial Intelligence and Statistics, 2018
892018
Parametric Gaussian Process Regressors
M Jankowiak, G Pleiss, JR Gardner
International Conference on Machine Learning, 2020
882020
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
822024
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
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
712022
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
622015
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
562020
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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Artikkelit 1–20