Dao-Hong Xiang

According to our database, Dao-Hong Xiang authored at least 14 papers between 2006 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2021

Comparison theorems on large-margin learning.

Amina Benabid, Jun Fan, Dao-Hong Xiang

Int. J. Wavelets Multiresolution Inf. Process., 2021

2019

Comparison theorems on large-margin learning.

Jun Fan, Dao-Hong Xiang

CoRR, 2019

2018

Total stability of kernel methods.

Andreas Christmann, Dao-Hong Xiang, Ding-Xuan Zhou

Neurocomputing, 2018

2016

Statistical consistency of coefficient-based conditional quantile regression.

Jia Cai, Dao-Hong Xiang

J. Multivar. Anal., 2016

A short note on extension theorems and their connection to universal consistency in machine learning.

Andreas Christmann, Florian Dumpert, Dao-Hong Xiang

CoRR, 2016

2013

Conditional quantiles with varying Gaussians.

Dao-Hong Xiang

Adv. Comput. Math., 2013

2012

Approximation Analysis of Learning Algorithms for Support Vector Regression and Quantile Regression.

Dao-Hong Xiang, Ting Hu, Ding-Xuan Zhou

J. Appl. Math., 2012

A new comparison theorem on conditional quantiles.

Dao-Hong Xiang

Appl. Math. Lett., 2012

2011

Logistic classification with varying Gaussians.

Dao-Hong Xiang

Comput. Math. Appl., 2011

Learning with varying insensitive loss.

Dao-Hong Xiang, Ting Hu, Ding-Xuan Zhou

Appl. Math. Lett., 2011

2010

Moving least-square method in learning theory.

Hong-Yan Wang, Dao-Hong Xiang, Ding-Xuan Zhou

J. Approx. Theory, 2010

2009

Classification with Gaussians and Convex Loss.

Dao-Hong Xiang, Ding-Xuan Zhou

J. Mach. Learn. Res., 2009

2008

Parzen windows for multi-class classification.

Zhi-Wei Pan, Dao-Hong Xiang, Quan-Wu Xiao, Ding-Xuan Zhou

J. Complex., 2008

2006

The consistency of multicategory support vector machines.

Di-Rong Chen, Dao-Hong Xiang

Adv. Comput. Math., 2006