Kun Chen

Orcid: 0000-0003-3579-5467

Affiliations:
  • University of Connecticut, Department of Statistics Storrs, CT, USA
  • University of Iowa, Iowa City, IA, USA (PhD 2011)


According to our database1, Kun Chen authored at least 16 papers between 2016 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2022
Fast Stagewise Sparse Factor Regression.
J. Mach. Learn. Res., 2022

Multivariate Functional Regression Via Nested Reduced-Rank Regularization.
J. Comput. Graph. Stat., 2022

Improving suicide risk prediction via targeted data fusion: proof of concept using medical claims data.
J. Am. Medical Informatics Assoc., 2022

Collaboration Equilibrium in Federated Learning.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021
Generalized co-sparse factor regression.
Comput. Stat. Data Anal., 2021

Correcting the User Feedback-Loop Bias for Recommendation Systems.
CoRR, 2021

Learning to Collaborate.
CoRR, 2021

2020
Statistically Guided Divide-and-Conquer for Sparse Factorization of Large Matrix.
CoRR, 2020

2019
SOFAR: Large-Scale Association Network Learning.
IEEE Trans. Inf. Theory, 2019

2018
Leveraging mixed and incomplete outcomes via reduced-rank modeling.
J. Multivar. Anal., 2018

Robust finite mixture regression for heterogeneous targets.
Data Min. Knowl. Discov., 2018

Boosted Sparse and Low-Rank Tensor Regression.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease.
Proceedings of the AMIA 2018, 2018

2017
Finite mixture modeling of censored data using the multivariate Student-t distribution.
J. Multivar. Anal., 2017

Bayesian sparse reduced rank multivariate regression.
J. Multivar. Anal., 2017

2016
Using Hospitalization and Suicide Mortality Data to Identify Subpopulation of High Suicide Risk via Survival Modeling.
Proceedings of the AMIA 2016, 2016


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