Zhaobin Kuang - RankMe

21 papers A* 5A 3C 1Journal 8Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Factor Learning Portfolio Optimization Informed by Continuous-Time Finance Models. Trans. Mach. Learn. Res. Sinong Geng, Houssam Nassif, Zhaobin Kuang, Anders Max Reppen, Ronnie Sircar
2023	A*	`conf`	SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding. KDD Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky
2023	J	`jnl`	SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding. CoRR Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky
2023	J	`jnl`	Trusted Source Alignment in Large Language Models. CoRR Vasilisa Bashlovkina, Zhaobin Kuang, Riley Matthews, Edward Clifford, Yennie Jun, William W. Cohen, Simon Baumgartner
2022	A	`conf`	Firebolt: Weak Supervision Under Weaker Assumptions. AISTATS Zhaobin Kuang, Chidubem G. Arachie, Bangyong Liang, Pradyumna Narayana, Giulia DeSalvo, Michael S. Quinn, Bert Huang, Geoffrey Downs, Yang Yang
2020	—	`conf`	Adverse drug reaction discovery from electronic health records with deep neural networks. CHIL Wei Zhang, Zhaobin Kuang, Peggy L. Peissig, David Page
2020	A	`conf`	Ivy: Instrumental Variable Synthesis for Causal Inference. AISTATS Zhaobin Kuang, Frederic Sala, Nimit Sharad Sohoni, Sen Wu, Aldo Córdova-Palomera, Jared Dunnmon, James Priest, Christopher Ré
2020	J	`jnl`	Ivy: Instrumental Variable Synthesis for Causal Inference. CoRR Zhaobin Kuang, Frederic Sala, Nimit Sharad Sohoni, Sen Wu, Aldo Córdova-Palomera, Jared Dunnmon, James Priest, Christopher Ré
2020	J	`jnl`	Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. CoRR Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page
2020	J	`jnl`	Temporal Poisson Square Root Graphical Models. CoRR Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page
2019	J	`jnl`	A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications. CoRR Finn Kuusisto, John W. Steill, Zhaobin Kuang, James A. Thomson, David Page, Ron M. Stewart
2019	J	`jnl`	High-Throughput Machine Learning from Electronic Health Records. CoRR Ross S. Kleiman, Paul S. Bennett, Peggy L. Peissig, Richard L. Berg, Zhaobin Kuang, Scott J. Hebbring, Michael D. Caldwell, David Page
2018	C	`conf`	Recursive Feature Elimination by Sensitivity Testing. ICMLA Nicholas Sean Escanilla, Lisa Hellerstein, Ross Kleiman, Zhaobin Kuang, James Shull, David Page
2018	A	`conf`	Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. UAI Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page
2018	A*	`conf`	Temporal Poisson Square Root Graphical Models. ICML Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page
2017	—	`conf`	A Screening Rule for l1-Regularized Ising Model Estimation. NIPS Zhaobin Kuang, Sinong Geng, David Page
2017	—	`conf`	A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications. CRI Finn Kuusisto, John W. Steill, Zhaobin Kuang, James A. Thomson, David Page, Ron M. Stewart
2017	—	`conf`	Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data. MLHC Yujia Bao, Zhaobin Kuang, Peggy L. Peissig, David Page, Rebecca Willett
2017	A*	`conf`	Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data. KDD Zhaobin Kuang, Peggy L. Peissig, Vítor Santos Costa, Richard Maclin, David Page
2016	A*	`conf`	Baseline Regularization for Computational Drug Repositioning with Longitudinal Observational Data. IJCAI Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page
2016	A*	`conf`	Computational Drug Repositioning Using Continuous Self-Controlled Case Series. KDD Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page