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Found 6 papers, 3 papers with code
Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting
A common network inference problem, arising from real-world data constraints, is how to infer a dynamic network from its time-aggregated adjacency matrix and time-varying marginals (i. e., row and column sums).
Machine Learning for Health symposium 2023 -- Findings track
A collection of the accepted Findings papers that were presented at the 3rd Machine Learning for Health symposium (ML4H 2023), which was held on December 10, 2023, in New Orleans, Louisiana, USA.
Accurate Measures of Vaccination and Concerns of Vaccine Holdouts from Web Search Logs
We find that holdouts, compared to early adopters matched on covariates, are 69% more likely to click on untrusted news sites.
Automatically Inferring Gender Associations from Language
In this paper, we pose the question: do people talk about women and men in different ways?
Detecting Gang-Involved Escalation on Social Media Using Context
Gang-involved youth in cities such as Chicago have increasingly turned to social media to post about their experiences and intents online.
Crowd-Sourced Iterative Annotation for Narrative Summarization Corpora
We present an iterative annotation process for producing aligned, parallel corpora of abstractive and extractive summaries for narrative.
