A Statistical Learning Theory Framework for Supervised Pattern Discovery

by Huggins, Jonathan H., Rudin, Cynthia
Published 2022

A Statistical Learning Theory Framework for Supervised Pattern Discovery

by Huggins, Jonathan H., Rudin, Cynthia
Published 2021

Risk and regret of hierarchical Bayesian learners

by Huggins, Jonathan H., Tenenbaum, Joshua B
Published 2017

PASS-GLM: Polynomial approximate sufficient statistics for scalable Bayesian GLM inference

by Huggins, Jonathan H., Broderick, Tamara A
Published 2020

Coresets for scalable Bayesian logistic regression

by Huggins, Jonathan H., Campbell, Trevor David, Broderick, Tamara A
Published 2021

Scalable Gaussian process inference with finite-data mean and variance guarantees

by Huggins, Jonathan H., Broderick, Tamara A, Campbell, Trevor David
Published 2020

Fast state-space methods for inferring dendritic synaptic connectivity

by Pakman, Ari, Smith, Carl, Paninski, Liam, Huggins, Jonathan H.
Published 2016

Data-dependent compression of random features for large-scale kernel approximation

by Agrawal, Raj, Campbell, Trevor David, Huggins, Jonathan H., Broderick, Tamara A
Published 2020

Bidirectional contact tracing could dramatically improve COVID-19 control

by Bradshaw, William J., Alley, Ethan C., Huggins, Jonathan H., Lloyd, Alun L., Esvelt, Kevin Michael
Published 2021