Wenxin Jiang

Affiliations:
  • Northwestern University, Department of Statistics, Evanston, IL, USA
  • Cornell University, Ithaca, NY, USA (PhD 1996)


According to our database1, Wenxin Jiang authored at least 27 papers between 1998 and 2021.

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

Timeline

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Bibliography

2021
Extended graphical lasso for multiple interaction networks for high dimensional omics data.
PLoS Comput. Biol., 2021

A Note on Comparison of F-measures.
CoRR, 2021

2020
Including a Nugget Effect in Lifted Brownian Covariance Models.
SIAM/ASA J. Uncertain. Quantification, 2020

Statistical Formulas for F Measures.
CoRR, 2020

2019
Multi-sense Definition Modeling using Word Sense Decompositions.
CoRR, 2019

2018
Bayesian Complex Network Community Detection Using Nonparametric Topic Model.
Proceedings of the Complex Networks and Their Applications VII, 2018

2017
Ultra-high dimensional variable selection with application to normative aging study: DNA methylation and metabolic syndrome.
BMC Bioinform., 2017

2016
On oracle property and asymptotic validity of Bayesian generalized method of moments.
J. Multivar. Anal., 2016

Generalized Gini Correlation and its Application in Data-Mining.
Data Min. Knowl. Discov., 2016

2013
General Oracle Inequalities for Gibbs Posterior with Application to Ranking.
Proceedings of the COLT 2013, 2013

2012
On Convergence Rates of Mixtures of Polynomial Experts.
Neural Comput., 2012

2011
Predicting Panel Data Binary Choice with the Gibbs Posterior.
Neural Comput., 2011

2009
On Uniform Deviations of General Empirical Risks with Unboundedness, Dependence, and High Dimensionality.
J. Mach. Learn. Res., 2009

2006
On the Consistency of Bayesian Variable Selection for High Dimensional Binary Regression and Classification.
Neural Comput., 2006

On Consistency of Bayesian Inference with Mixtures of Logistic Regression.
Neural Comput., 2006

A note on mixtures of experts for multiclass responses: approximation rate and Consistent Bayesian Inference.
Proceedings of the Machine Learning, 2006

2004
Boosting with Noisy Data: Some Views from Statistical Theory.
Neural Comput., 2004

2002
Factorial Hidden Markov Models and the Generalized Backfitting Algorithm.
Neural Comput., 2002

2001
Some Theoretical Aspects of Boosting in the Presence of Noisy Data.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

Is regularization unnecessary for boosting?.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
On the asymptotic normality of hierarchical mixtures-of-experts for generalized linear models.
IEEE Trans. Inf. Theory, 2000

The VC Dimension for Mixtures of Binary Classifiers.
Neural Comput., 2000

Some Results on Weakly Accurate Base Learners for Boosting Regression and Classification.
Proceedings of the Multiple Classifier Systems, First International Workshop, 2000

1999
On the identifiability of mixtures-of-experts.
Neural Networks, 1999

On the Approximation Rate of Hierarchical Mixtures-of-Experts for Generalized Linear Models.
Neural Comput., 1999

Hierarchical mixtures-of-experts for generalized linear models: some results on denseness and consistency.
Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

1998
Hierarchical Mixtures-of-Experts for Exponential Family Regression Models with Generalized Linear Mean Functions: A Survey of Approximation and Consistency Results.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998


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