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Scaling Gaussian Processes with Derivative Information Using Variational Inference


Jul 08, 2021
Misha Padidar, Xinran Zhu, Leo Huang, Jacob R. Gardner, David Bindel


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Reducing the Variance of Gaussian Process Hyperparameter Optimization with Preconditioning


Jul 01, 2021
Jonathan Wenger, Geoff Pleiss, Philipp Hennig, John P. Cunningham, Jacob R. Gardner


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Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees


Jun 29, 2020
Shali Jiang, Daniel R. Jiang, Maximilian Balandat, Brian Karrer, Jacob R. Gardner, Roman Garnett


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Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization


Jun 19, 2020
Geoff Pleiss, Martin Jankowiak, David Eriksson, Anil Damle, Jacob R. Gardner


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Deep Sigma Point Processes


Feb 21, 2020
Martin Jankowiak, Geoff Pleiss, Jacob R. Gardner

* 14 pages, 10 figures 

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Sparse Gaussian Process Regression Beyond Variational Inference


Oct 16, 2019
Martin Jankowiak, Geoff Pleiss, Jacob R. Gardner

* 13 pages, 9 figures 

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Simple Black-box Adversarial Attacks


May 17, 2019
Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger

* Published at ICML 2019 

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Exact Gaussian Processes on a Million Data Points


Mar 19, 2019
Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson


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GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration


Oct 29, 2018
Jacob R. Gardner, Geoff Pleiss, David Bindel, Kilian Q. Weinberger, Andrew Gordon Wilson

* NIPS 2018 

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Constant-Time Predictive Distributions for Gaussian Processes


Jun 20, 2018
Geoff Pleiss, Jacob R. Gardner, Kilian Q. Weinberger, Andrew Gordon Wilson

* ICML 2018 

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Product Kernel Interpolation for Scalable Gaussian Processes


Feb 24, 2018
Jacob R. Gardner, Geoff Pleiss, Ruihan Wu, Kilian Q. Weinberger, Andrew Gordon Wilson

* Appears in Artificial Intelligence and Statistics (AISTATS) 21, 2018 

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Deep Manifold Traversal: Changing Labels with Convolutional Features


Mar 17, 2016
Jacob R. Gardner, Paul Upchurch, Matt J. Kusner, Yixuan Li, Kilian Q. Weinberger, Kavita Bala, John E. Hopcroft


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Differentially Private Bayesian Optimization


Feb 23, 2015
Matt J. Kusner, Jacob R. Gardner, Roman Garnett, Kilian Q. Weinberger


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Compressed Support Vector Machines


Feb 02, 2015
Zhixiang Xu, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger


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A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing


Sep 06, 2014
Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen

* 10 pages 

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Parallel Support Vector Machines in Practice


Apr 03, 2014
Stephen Tyree, Jacob R. Gardner, Kilian Q. Weinberger, Kunal Agrawal, John Tran

* 10 pages 

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