Jacob R. Gardner

发表

Compressed Support Vector Machines pdf

Stephen Tyree, Kilian Q. Weinberger, Zhixiang Eddie Xu, 2015, ArXiv.

Deep Manifold Traversal: Changing Labels with Convolutional Features pdf

Matt J. Kusner, Kilian Q. Weinberger, John E. Hopcroft, 2015, ArXiv.

Psychophysical Detection Testing with Bayesian Active Learning

Kilian Q. Weinberger, John P. Cunningham, Xinyu Song, 2015, UAI.

Deep Sigma Point Processes pdf

Jacob R. Gardner, Martin Jankowiak, Geoff Pleiss, 2020, UAI.

WOODSTOCC: Extracting Latent Parallelism from a DNA Sequence Aligner on a GPU

Jeremy Buhler, Jacob R. Gardner, Stephen V. Cole, 2014, 2014 IEEE 13th International Symposium on Parallel and Distributed Computing.

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

Andrew Gordon Wilson, Kilian Q. Weinberger, David Bindel, 2018, NeurIPS.

Differentially Private Bayesian Optimization

Roman Garnett, Matt J. Kusner, Kilian Q. Weinberger, 2015, ICML.

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

Yixin Chen, Wenlin Chen, Kilian Q. Weinberger, 2014, AAAI.

Discovering and Exploiting Additive Structure for Bayesian Optimization

Roman Garnett, Kilian Q. Weinberger, Roger B. Grosse, 2017, AISTATS.

Constant-Time Predictive Distributions for Gaussian Processes

Andrew Gordon Wilson, Kilian Q. Weinberger, Jacob R. Gardner, 2018, ICML.

Exact Gaussian Processes on a Million Data Points

Stephen Tyree, Andrew Gordon Wilson, Kilian Q. Weinberger, 2019, NeurIPS.

Parallel Support Vector Machines in Practice pdf

Stephen Tyree, Kilian Q. Weinberger, John Tran, 2014, ArXiv.

Bayesian Active Model Selection with an Application to Automated Audiometry

Roman Garnett, Gustavo Malkomes, Kilian Q. Weinberger, 2015, NIPS.

Simple Black-box Adversarial Attacks

Andrew Gordon Wilson, Kilian Q. Weinberger, Chuan Guo, 2019, ICML.

Bayesian Optimization with Inequality Constraints

Matt J. Kusner, Kilian Q. Weinberger, John P. Cunningham, 2014, ICML.

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

Roman Garnett, Brian Karrer, Maximilian Balandat, 2020, NeurIPS.

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

Anil Damle, Jacob R. Gardner, Martin Jankowiak, 2020, NeurIPS.

Product Kernel Interpolation for Scalable Gaussian Processes

Andrew Gordon Wilson, Kilian Q. Weinberger, Jacob R. Gardner, 2018, AISTATS.

Parametric Gaussian Process Regressors

Jacob R. Gardner, Martin Jankowiak, Geoff Pleiss, 2020, ICML.

Scaling Gaussian Processes with Derivative Information Using Variational Inference pdf

David Bindel, Jacob R. Gardner, Misha Padidar, 2021, NeurIPS.

Reducing the Variance of Gaussian Process Hyperparameter Optimization with Preconditioning pdf

John P. Cunningham, Philipp Hennig, Jacob R. Gardner, 2021, ArXiv.

Fast, Continuous Audiogram Estimation Using Machine Learning

Kilian Q. Weinberger, Jacob R. Gardner, D. Barbour, 2015, Ear and hearing.

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

Anil Damle, Jacob R. Gardner, Martin Jankowiak, 2020, NeurIPS.

Parametric Gaussian Process Regressors

Jacob R. Gardner, Martin Jankowiak, Geoff Pleiss, 2020, ICML.

Determining subpopulation methylation profiles from bisulfite sequencing data of heterogeneous samples using DXM

Kilian Q. Weinberger, Jacob R. Gardner, Jared M. Andrews, 2020, bioRxiv.

Preconditioning for Scalable Gaussian Process Hyperparameter Optimization

Jacob R. Gardner, J. Cunningham, Philipp Hennig, 2021, 2107.00243.

Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients

Jacob R. Gardner, Adji Bousso Dieng, Jisu Oh, 2022, ArXiv.

Preconditioning for Scalable Gaussian Process Hyperparameter Optimization

Jacob R. Gardner, J. Cunningham, Philipp Hennig, 2021, ICML.

Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients

Jacob R. Gardner, Adji Bousso Dieng, Jisu Oh, 2022, ArXiv.

Extracting or Guessing? Improving Faithfulness of Event Temporal Relation Extraction

Jacob R. Gardner, D. Roth, Muhao Chen, 2022, EACL.

Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients

Jacob R. Gardner, Adji Bousso Dieng, Jisu Oh, 2022, NeurIPS.

Discovering Many Diverse Solutions with Bayesian Optimization

Jacob R. Gardner, David Eriksson, Kaiwen Wu, 2022, 2210.10953.

Scalable Global Optimization via Local Bayesian Optimization

Matthias Poloczek, Michael Pearce, David Eriksson, 2019, NeurIPS.

Discovering Many Diverse Solutions with Bayesian Optimization

Jacob R. Gardner, David Eriksson, Kaiwen Wu, 2022, AISTATS.