Zhaobin Kuang

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 20

Top Topics

Causal Inference

Observational Data

Top Venues

Publications

Vasilisa Bashlovkina, Zhaobin Kuang, Riley Matthews, Edward Clifford, Yennie Jun, William W. Cohen, Simon Baumgartner
Trusted Source Alignment in Large Language Models. CoRR (2023)
Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky
SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding. CoRR (2023)
Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky
SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding. KDD (2023)
Zhaobin Kuang, Chidubem G. Arachie, Bangyong Liang, Pradyumna Narayana, Giulia DeSalvo, Michael S. Quinn, Bert Huang, Geoffrey Downs, Yang Yang
Firebolt: Weak Supervision Under Weaker Assumptions. AISTATS (2022)
Wei Zhang, Zhaobin Kuang, Peggy L. Peissig, David Page
Adverse drug reaction discovery from electronic health records with deep neural networks. CHIL (2020)
Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page
Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. CoRR (2020)
Zhaobin Kuang, Frederic Sala, Nimit Sharad Sohoni, Sen Wu, Aldo Córdova-Palomera, Jared Dunnmon, James Priest, Christopher Ré
Ivy: Instrumental Variable Synthesis for Causal Inference. AISTATS (2020)
Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page
Temporal Poisson Square Root Graphical Models. CoRR (2020)
Zhaobin Kuang, Frederic Sala, Nimit Sharad Sohoni, Sen Wu, Aldo Córdova-Palomera, Jared Dunnmon, James Priest, Christopher Ré
Ivy: Instrumental Variable Synthesis for Causal Inference. CoRR (2020)
Ross S. Kleiman, Paul S. Bennett, Peggy L. Peissig, Richard L. Berg, Zhaobin Kuang, Scott J. Hebbring, Michael D. Caldwell, David Page
High-Throughput Machine Learning from Electronic Health Records. CoRR (2019)
Finn Kuusisto, John W. Steill, Zhaobin Kuang, James A. Thomson, David Page, Ron M. Stewart
A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications. CoRR (2019)
Nicholas Sean Escanilla, Lisa Hellerstein, Ross Kleiman, Zhaobin Kuang, James Shull, David Page
Recursive Feature Elimination by Sensitivity Testing. ICMLA (2018)
Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page
Temporal Poisson Square Root Graphical Models. ICML (2018)
Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page
Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. UAI (2018)
Zhaobin Kuang, Sinong Geng, David Page
A Screening Rule for l1-Regularized Ising Model Estimation. NIPS (2017)
Yujia Bao, Zhaobin Kuang, Peggy L. Peissig, David Page, Rebecca Willett
Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data. MLHC (2017)
Finn Kuusisto, John W. Steill, Zhaobin Kuang, James A. Thomson, David Page, Ron M. Stewart
A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications. CRI (2017)
Zhaobin Kuang, Peggy L. Peissig, Vítor Santos Costa, Richard Maclin, David Page
Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data. KDD (2017)
Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page
Baseline Regularization for Computational Drug Repositioning with Longitudinal Observational Data. IJCAI (2016)
Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page
Computational Drug Repositioning Using Continuous Self-Controlled Case Series. KDD (2016)