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ORCIDZhaobin Kuang
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2020 – today
- 2023
[c13]Vasilisa Bashlovkina
, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky:
SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding. KDD 2023: 3737-3749- [i7]Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky:
SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding. CoRR abs/2307.00135 (2023) - [i6]Vasilisa Bashlovkina, Zhaobin Kuang, Riley Matthews, Edward Clifford, Yennie Jun, William W. Cohen, Simon Baumgartner:
Trusted Source Alignment in Large Language Models. CoRR abs/2311.06697 (2023) - 2022
- [c12]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: 8214-8259 - 2020
- [c11]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: 398-410 - [c10]Wei Zhang, Zhaobin Kuang, Peggy L. Peissig, David Page:
Adverse drug reaction discovery from electronic health records with deep neural networks. CHIL 2020: 30-39 - [i5]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 abs/2004.05316 (2020) - [i4]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 abs/2005.06083 (2020) - [i3]Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page:
Temporal Poisson Square Root Graphical Models. CoRR abs/2005.06462 (2020)
2010 – 2019
- 2019
- [i2]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 abs/1906.05255 (2019) - [i1]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 abs/1907.01901 (2019) - 2018
- [c9]Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page:
Temporal Poisson Square Root Graphical Models. ICML 2018: 1700-1709 - [c8]Nicholas Sean Escanilla, Lisa Hellerstein, Ross Kleiman, Zhaobin Kuang, James Shull, David Page:
Recursive Feature Elimination by Sensitivity Testing. ICMLA 2018: 40-47 - [c7]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: 156-166 - 2017
- [c6]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 - [c5]Zhaobin Kuang, Peggy L. Peissig, Vítor Santos Costa, Richard Maclin, David Page:
Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data. KDD 2017: 1537-1546 - [c4]Yujia Bao, Zhaobin Kuang, Peggy L. Peissig, David Page, Rebecca Willett:
Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data. MLHC 2017: 177-190 - [c3]Zhaobin Kuang, Sinong Geng, David Page:
A Screening Rule for l1-Regularized Ising Model Estimation. NIPS 2017: 720-731 - 2016
- [c2]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: 2521-2528 - [c1]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: 491-500
Coauthor Index
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