Xin Dang

According to our database1, Xin Dang authored at least 25 papers between 2007 and 2018.

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



In proceedings 
PhD thesis 




Robust and Efficient Boosting Method Using the Conditional Risk.
IEEE Trans. Neural Netw. Learning Syst., 2018

Robust and Efficient Boosting Method using the Conditional Risk.
CoRR, 2018

Pareto cascade modeling of diffusion networks.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Recognition Influence of Different Acousitc Characters between Male and Female Speakers.
Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence, 2018

Integration of Cancer Data through Multiple Mixed Graphical Model.
Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018

An efficient movement and mental classification for children with autism based on motion and EEG features.
J. Ambient Intelligence and Humanized Computing, 2017

Label confidence based AdaBoost algorithm.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

An image reconstruction framework based on deep neural network for electrical impedance tomography.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

A robust speech watermarking based on Quantization Index Modulation and Double Discrete Cosine Transform.
Proceedings of the 10th International Congress on Image and Signal Processing, 2017

Robust Model-Based Learning via Spatial-EM Algorithm.
IEEE Trans. Knowl. Data Eng., 2015

A generative Bayesian model to identify cancer driver genes.
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015

Financial ratio selection for business failure prediction using soft set theory.
Knowl.-Based Syst., 2014

Noise Power Spectral Density Estimation Using the Generalized Gamma Probability Density Function and Minimum Mean Square Error.
IEICE Transactions, 2014

Learning accurate and interpretable models based on regularized random forests regression.
BMC Systems Biology, 2014

Rule based regression and feature selection for biological data.
Proceedings of the 2013 IEEE International Conference on Bioinformatics and Biomedicine, 2013

Multiclass classification with potential function rules: Margin distribution and generalization.
Pattern Recognition, 2012

The prediction for listed companies' financial distress by using multiple prediction methods with rough set and Dempster-Shafer evidence theory.
Knowl.-Based Syst., 2012

Leveraging domain information to restructure biological prediction.
BMC Bioinformatics, 2011

Noise reduction using modified phase spectra and Wiener Filter.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

Projection based scatter depth functions and associated scatter estimators.
J. Multivariate Analysis, 2010

Learning to rank using 1-norm regularization and convex hull reduction.
Proceedings of the 48th Annual Southeast Regional Conference, 2010

Outlier Detection with the Kernelized Spatial Depth Function.
IEEE Trans. Pattern Anal. Mach. Intell., 2009

Graph ranking for exploratory gene data analysis.
BMC Bioinformatics, 2009

Robust clustering in high dimensional data using statistical depths.
BMC Bioinformatics, 2007

Depth-Based Novelty Detection and Its Application to Taxonomic Research.
Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007