Zhaobin Kuang

According to our database, Zhaobin Kuang authored at least 15 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2023

Trusted Source Alignment in Large Language Models.

Vasilisa Bashlovkina, Zhaobin Kuang, Riley Matthews, Edward Clifford, Yennie Jun, William W. Cohen, Simon Baumgartner

CoRR, 2023

SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding.

Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Firebolt: Weak Supervision Under Weaker Assumptions.

Zhaobin Kuang, Chidubem G. Arachie, Bangyong Liang, Pradyumna Narayana, Giulia DeSalvo, Michael S. Quinn, Bert Huang, Geoffrey Downs, Yang Yang

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

2020

Adverse drug reaction discovery from electronic health records with deep neural networks.

Wei Zhang, Zhaobin Kuang, Peggy L. Peissig, David Page

Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

Ivy: Instrumental Variable Synthesis for Causal Inference.

Zhaobin Kuang, Frederic Sala, Nimit Sharad Sohoni, Sen Wu, Aldo Córdova-Palomera, Jared Dunnmon, James Priest, Christopher Ré

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

High-Throughput Machine Learning from Electronic Health Records.

Ross S. Kleiman, Paul S. Bennett, Peggy L. Peissig, Richard L. Berg, Zhaobin Kuang, Scott J. Hebbring, Michael D. Caldwell, David Page

CoRR, 2019

2018

Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error.

Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Recursive Feature Elimination by Sensitivity Testing.

Nicholas Sean Escanilla, Lisa Hellerstein, Ross Kleiman, Zhaobin Kuang, James Shull, David Page

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Temporal Poisson Square Root Graphical Models.

Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

A Screening Rule for l1-Regularized Ising Model Estimation.

Zhaobin Kuang, Sinong Geng, David Page

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data.

Yujia Bao, Zhaobin Kuang, Peggy L. Peissig, David Page, Rebecca Willett

Proceedings of the Machine Learning for Health Care Conference, 2017

Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data.

Zhaobin Kuang, Peggy L. Peissig, Vítor Santos Costa, Richard Maclin, David Page

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications.

Finn Kuusisto, John W. Steill, Zhaobin Kuang, James A. Thomson, David Page, Ron M. Stewart

Proceedings of the Summit on Clinical Research Informatics, 2017

2016

Computational Drug Repositioning Using Continuous Self-Controlled Case Series.

Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Baseline Regularization for Computational Drug Repositioning with Longitudinal Observational Data.

Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016