David Bruns-Smith

According to our database, David Bruns-Smith authored at least 14 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Deconfounding Scores and Representation Learning for Causal Effect Estimation with Weak Overlap.

Oscar Clivio, Alexander D'Amour, Alexander Franks, David Bruns-Smith, Christopher C. Holmes, Avi Feller

CoRR, April, 2026

2025

Ridge Boosting is Both Robust and Efficient.

David Bruns-Smith, Zhongming Xie, Avi Feller

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2023

Augmented balancing weights as linear regression.

David Bruns-Smith, Oliver Dukes, Avi Feller, Elizabeth L. Ogburn

CoRR, 2023

Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders.

David Bruns-Smith, Angela Zhou

CoRR, 2023

Using Supervised Learning to Estimate Inequality in the Size and Persistence of Income Shocks.

David Bruns-Smith, Avi Feller, Emi Nakamura

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

Outcome Assumptions and Duality Theory for Balancing Weights.

David A. Bruns-Smith, Avi Feller

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Accelerating Genomic Data Analytics With Composable Hardware Acceleration Framework.

Tae Jun Ham, Yejin Lee, Seong Hoon Seo, U. Gyeong Song, Jae W. Lee, David Bruns-Smith, Brendan Sweeney, Krste Asanovic, Young H. Oh, Lisa Wu Wills

IEEE Micro, 2021

Model-Free and Model-Based Policy Evaluation when Causality is Uncertain.

David Bruns-Smith

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Genesis: A Hardware Acceleration Framework for Genomic Data Analysis.

Tae Jun Ham, David Bruns-Smith, Brendan Sweeney, Yejin Lee, Seong Hoon Seo, U. Gyeong Song, Young H. Oh, Krste Asanovic, Jae W. Lee, Lisa Wu Wills

Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

2019

Enhancing Network Visibility and Security through Tensor Analysis.

Muthu Manikandan Baskaran, Thomas Henretty, James R. Ezick, Richard Lethin, David Bruns-Smith

Future Gener. Comput. Syst., 2019

FPGA Accelerated INDEL Realignment in the Cloud.

Lisa Wu, David Bruns-Smith, Frank A. Nothaft, Qijing Huang, Sagar Karandikar, Johnny Le, Andrew Lin, Howard Mao, Brendan Sweeney, Krste Asanovic, David A. Patterson, Anthony D. Joseph

Proceedings of the 25th IEEE International Symposium on High Performance Computer Architecture, 2019

2017

A quantitative and qualitative analysis of tensor decompositions on spatiotemporal data.

Tom Henretty, Muthu Manikandan Baskaran, James R. Ezick, David Bruns-Smith, Tyler A. Simon

Proceedings of the 2017 IEEE High Performance Extreme Computing Conference, 2017

Memory-efficient parallel tensor decompositions.

Muthu Manikandan Baskaran, Tom Henretty, Benoît Pradelle, Matthew Harper Langston, David Bruns-Smith, James R. Ezick, Richard Lethin

Proceedings of the 2017 IEEE High Performance Extreme Computing Conference, 2017

2016

Accelerated low-rank updates to tensor decompositions.

Muthu Manikandan Baskaran, Matthew Harper Langston, Tahina Ramananandro, David Bruns-Smith, Tom Henretty, James R. Ezick, Richard Lethin

Proceedings of the 2016 IEEE High Performance Extreme Computing Conference, 2016