31 citations · 57 across the 7 of their papers we have counts for
7 papers
SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding
Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang +2
We study the ability of transformer-based language models (LMs) to understand social media language. Social media (SM) language is distinct from standard written language, yet exis…
Temporal Poisson Square Root Graphical Models
Sinong Geng, Zhaobin Kuang, Peggy Peissig +1
We propose temporal Poisson square root graphical models (TPSQRs), a generalization of Poisson square root graphical models (PSQRs) specifically designed for modeling longitudinal…
Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error
Sinong Geng, Zhaobin Kuang, Jie Liu +2
We study the -regularized maximum likelihood estimator/estimation (MLE) problem for discrete Markov random fields (MRFs), where efficient and scalable learning requires both s…
Ivy: Instrumental Variable Synthesis for Causal Inference
Zhaobin Kuang, Frederic Sala, Nimit Sohoni +5
A popular way to estimate the causal effect of a variable x on y from observational data is to use an instrumental variable (IV): a third variable z that affects y only through x.…
High-Throughput Machine Learning from Electronic Health Records
Ross S. Kleiman, Paul S. Bennett, Peggy L. Peissig +5
The widespread digitization of patient data via electronic health records (EHRs) has created an unprecedented opportunity to use machine learning algorithms to better predict disea…
A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications
Finn Kuusisto, John Steill, Zhaobin Kuang +3
We present a simple text mining method that is easy to implement, requires minimal data collection and preparation, and is easy to use for proposing ranked associations between a l…
Computational Drug Repositioning Using Continuous Self-controlled Case Series
Zhaobin Kuang, James Thomson, Michael Caldwell +3
Computational Drug Repositioning (CDR) is the task of discovering potential new indications for existing drugs by mining large-scale heterogeneous drug-related data sources. Levera…