The Behavior and Convergence of Local Bayesian Optimization[Paper]
Kaiwen Wu, Kyurae Kim, Roman Garnett, Jacob R. Gardner
Neural Information Processing Systems (NeurIPS 2023, to appear).
Variational Gaussian Processes with Decoupled Conditionals[Paper]
Xinran Zhu, Kaiwen Wu, Natalie Maus, Jacob R. Gardner, David Bindel
Neural Information Processing Systems (NeurIPS 2023, to appear).
On the Convergence of Black-Box Variational Inference[Paper]
Kyurae Kim, Jisu Oh, Kaiwen Wu, Yian Ma, Jacob R. Gardner
Neural Information Processing Systems (NeurIPS 2023, to appear).
Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference.[Paper]
Kyurae Kim, Kaiwen Wu, Jisu Oh, Jacob R. Gardner
International Conference on Machine Learning (ICML 2023). Oral.
Adversarial Prompting for Black Box Foundation Models[Paper]
Natalie Maus, Patrick Chao, Eric Wong, Jacob Gardner
(Preprint).
Discovering Many Diverse Solutions with Bayesian Optimization[Paper]
Natalie Maus, Kaiwen Wu, David Eriksson, Jacob Gardner
Artificial Intelligence and Statistics (AISTATS 2023). Notable paper.
Local Latent Space Bayesian Optimization over Structured Inputs[Paper]
Natalie Maus, Haydn T Jones, Juston S Moore, Matt J Kusner, John Bradshaw, Jacob R Gardner
Neural Information Processing Systems (NeurIPS 2022).
Local Bayesian optimization via maximizing probability of descent[Paper]
Quan Nguyen, Kaiwen Wu, Jacob R Gardner, Roman Garnett
Neural Information Processing Systems (NeurIPS 2022). Oral.
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients[Paper]
Kyurae Kim, Jisu Oh, Jacob R Gardner, Adji Bousso Dieng, Hongseok Kim
Neural Information Processing Systems (NeurIPS 2022).
Preconditioning for Scalable Gaussian Process Hyperparameter Optimization[Paper]
Jonathan Wenger, Geoff Pleiss, Philipp Hennig, John P Cunningham, Jacob R Gardner
International Conference on Machine Learning (ICML 2022). Long talk.
Extracting or Guessing? Improving Faithfulness of Event Temporal Relation Extraction[Paper]
Haoyu Wang, Hongming Zhang, Yuqian Deng, Jacob R Gardner, Muhao Chen, Dan Roth
(Preprint.)
Scaling gaussian processes with derivative information using variational inference[Paper]
Misha Padidar, Xinran Zhu, Leo Huang, Jacob Gardner, David Bindel
Neural Information Processing Systems (NeurIPS 2021).
Determining subpopulation methylation profiles from bisulfite sequencing data of heterogeneous samples using DXM[Paper]
Jerry Fong, Jacob R Gardner, Jared M Andrews, Amanda F Cashen, Jacqueline E Payton, Kilian Q Weinberger, John R Edwards
Nucleic Acids Research (2021).
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees[Paper]
Shali Jiang, Daniel R Jiang, Maximilian Balandat, Brian Karrer, Jacob R Gardner, Roman Garnett
Neural Information Processing Systems (NeurIPS 2020).
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization[Paper]
Geoff Pleiss, Martin Jankowiak, David Eriksson, Anil Damle, Jacob R. Gardner
Neural Information Processing Systems (NeurIPS 2020).
Deep Sigma Point Processes[Paper]
Martin Jankowiak, Geoff Pleiss, Jacob R. Gardner
Conference on Uncertainty in Artifical Intelligence (UAI 2020).
Parametric Gaussian Process Regressors [Paper]
Martin Jankowiak, Geoff Pleiss, Jacob R. Gardner
International Conference on Machine Learning (ICML 2020).
Scalable Global Optimization via Local Bayesian Optimization [Paper]
David Eriksson, Michael Pearce, Jacob R. Gardner, Ryan Turner, Matthias Poloczek
Neurial Information Processing Systems (NeurIPS 2019) Spotlight.
Exact Gaussian Processes on a Million Data Points [Paper]
Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew G. Wilson
Neurial Information Processing Systems (NeurIPS 2019)
Simple Blackbox Adversarial Attacks [Paper]
Chuan Guo, Jacob R. Gardner, Yurong You, Andrew G. Wilson, Kilian Q. Weinberger
International Conference on Machine Learning (ICML 2019).
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration [Paper]
Jacob R. Gardner, Geoff Pleiss, Kilian Q. Weinberger, David Bindel, Andrew G. Wilson
Neurial Information Processing Systems (NeurIPS 2018). Spotlight.
Constant Time Predictive Distributions for Gaussian Processes [Paper]
Geoff Pleiss, Jacob R. Gardner, Kilian Q. Weinberger, Andrew G. Wilson
International Conference on Machine Learning (ICML 2018).
Product Kernel Interpolation for Scalable Gaussian Processes [Paper]
Jacob R. Gardner, Geoff Pleiss, Ruihan Wu, Kilian Q. Weinberger, Andrew G. Wilson
Artificial Intelligence and Statistics (AISTATS 2018)
Discovering and Exploiting Additive Structure for Bayesian Optimization [Paper]
Jacob R. Gardner, Chuan Guo, Kilian Q. Weinberger, Roman Garnett, Roger Grosse
Artificial Intelligence and Statistics (AISTATS 2017)
Bayesian Active Model Selection with an Application to Automated Audiometry [Paper]
Jacob R. Gardner, Gustavo Malkomes, Roman Garnett, Kilian Q. Weinberger, Dennis Barbour, John P. Cunningham
Neural Information Processing Systems (NeurIPS 2015)
Psychophysical Detection Testing with Bayesian Active Learning [Paper]
Jacob R. Gardner, Xinyu Song, Kilian Q. Weinberger, Dennis Barbour, John P. Cunningham
Uncertainty in Artifical Intelligence (UAI 2015)
Deep feature interpolation for image content changes [Paper]
Paul Upchurch*, Jacob R. Gardner*, Kavita Bala, Robert Pless, Noah Snavely, Kilian Q. Weinberger
Computer Vision and Pattern Recognition (CVPR 2016)
* authors contributed equally
Deep manifold traversal: Changing labels with convolutional features [Paper]
Jacob R. Gardner*, Paul Upchurch*, Matt J. Kusner, Yixuan Li, Kilian Q. Weinberger, Kavita Bala, John E. Hopcroft
* authors contributed equally
Differentially Private Bayesian Optimization [Paper]
Matthew J. Kusner, Jacob R. Gardner, Roman Garnett, Kilian Q. Weinberger
International Conference on Machine Learning (ICML 2015)
A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing. [Paper]
Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen
Association for the Advancement of Artificial Intelligence (AAAI 2015)
Bayesian Optimization with Inequality Constraints. [Paper]
Jacob R. Gardner, Matt J. Kusner, Zhixiang Xu, Kilian Q. Weinberger, John P. Cunningham
International Conference on Machine Learning (ICML 2014)