Cheng Cheng

Orcid: 0000-0002-1876-0855

Affiliations:
  • Carnegie Mellon University, Pittsburgh, PA, USA


According to our database1, Cheng Cheng authored at least 13 papers between 2017 and 2023.

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Bibliography

2023
Typed Markers and Context for Clinical Temporal Relation Extraction.
Proceedings of the Machine Learning for Healthcare Conference, 2023

Individual Fairness Under Uncertainty.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022
Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19.
Proceedings of the AMIA 2022, 2022

2021
SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection.
Proceedings of Machine Learning and Systems 2021, 2021

Unpacking the Drop in COVID-19 Case Fatality Rates: A Study of National and Florida Line-Level Data.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

Disentangled Hyperspherical Clustering for Sepsis Phenotyping.
Proceedings of the Artificial Intelligence in Medicine, 2021

2020
Predicting Mortality Risk in Viral and Unspecified Pneumonia to Assist Clinicians with COVID-19 ECMO Planning.
CoRR, 2020

SUOD: A Scalable Unsupervised Outlier Detection Framework.
CoRR, 2020

Mortality Risk Score for Critically Ill Patients with Viral or Unspecified Pneumonia: Assisting Clinicians with COVID-19 ECMO Planning.
Proceedings of the Artificial Intelligence in Medicine, 2020

Combining Machine Learning Models Using combo Library.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2018
Message Passing Algorithms for Semiring-Based and Valued Constraint Satisfaction Problems.
Proceedings of the Eleventh International Symposium on Combinatorial Search, 2018

The Buss Reduction for the k-Weighted Vertex Cover Problem.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2018

2017
Measuring Territorial Control in Civil Wars Using Hidden Markov Models: A Data Informatics-Based Approach.
CoRR, 2017


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