Yuhong Yang

Orcid: 0000-0003-3618-3083

Affiliations:
  • University of Minnesota, School of Statistics, Minnesota, MN, USA
  • Yale University, New Haven, CT, USA (PhD 1996)


According to our database1, Yuhong Yang authored at least 30 papers between 1998 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Golden Ratio-Based Sufficient Dimension Reduction.
CoRR, 2024

Drift to Remember.
CoRR, 2024

Additive-Effect Assisted Learning.
CoRR, 2024

2023
Optimal Integrating Learning for Split Questionnaire Design Type Data.
J. Comput. Graph. Stat., 2023

Multifold Cross-Validation Model Averaging for Generalized Additive Partial Linear Models.
J. Comput. Graph. Stat., 2023

Pruning Deep Neural Networks from a Sparsity Perspective.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Parallel Assisted Learning.
IEEE Trans. Signal Process., 2022

Profile electoral college cross-validation.
Inf. Sci., 2022

A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation.
CoRR, 2022

2021
Estimating and forecasting dynamic correlation matrices: A nonlinear common factor approach.
J. Multivar. Anal., 2021

Targeted Cross-Validation.
CoRR, 2021

A Stabilized Dense Network Approach for High-Dimensional Prediction.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
To update or not to update? Delayed Nonparametric Bandits with Randomized Allocation.
CoRR, 2020

Confidence Calibration on Multiclass Classification in Medical Imaging.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019
High-Dimensional Adaptive Minimax Sparse Estimation With Interactions.
IEEE Trans. Inf. Theory, 2019

A Binary Regression Adaptive Goodness-of-fit Test (BAGofT).
CoRR, 2019

Randomized Allocation with Nonparametric Estimation for Contextual Multi-Armed Bandits with Delayed Rewards.
CoRR, 2019

2018
Model Selection Techniques: An Overview.
IEEE Signal Process. Mag., 2018

2017
Anomaly Detection for Categorical Observations Using Latent Gaussian Process.
Proceedings of the Neural Information Processing - 24th International Conference, 2017

2016
Kernel Estimation and Model Combination in A Bandit Problem with Covariates.
J. Mach. Learn. Res., 2016

2015
Variable selection after screening: with or without data splitting?
Comput. Stat., 2015

2014
Adaptive minimax regression estimation over sparse lq-hulls.
J. Mach. Learn. Res., 2014

2013
Metric entropy and sparse linear approximation of l<sub>q</sub>-hulls for 0<q≤1.
J. Approx. Theory, 2013

2012
Randomized allocation with dimension reduction in a bandit problem with covariates.
Proceedings of the 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012

2007
How Powerful Can Any Regression Learning Procedure Be?.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

2001
Minimax rate adaptive estimation over continuous hyper-parameters.
IEEE Trans. Inf. Theory, 2001

2000
Comment on "Finite sample performance guarantees of fusers for function estimators" [Information Fusion 1: 35-44 (2000)].
Inf. Fusion, 2000

1999
Minimax nonparametric classification - Part II: Model selection for adaptation.
IEEE Trans. Inf. Theory, 1999

Minimax nonparametric classification - Part I: Rates of convergence.
IEEE Trans. Inf. Theory, 1999

1998
An Asymptotic Property of Model Selection Criteria.
IEEE Trans. Inf. Theory, 1998


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