Ling Zhen

发表

Multiple Instance Learning via Multiple Kernel Learning *

Ling Jing, Bing Yang, Qian Li, 2010 .

Adaptive feature selection via a new version of support vector machine

Zhiqiang Zhang, Chunhua Zhang, Ling Zhen, 2012, Neural Computing and Applications.

Adaptive feature selection via a new version of support vector machine

N. Deng, Chunhua Zhang, Junyan Tan, 2013, Neural Computing and Applications.

A novel projection nonparallel support vector machine for pattern classification

Liming Liu, Ling Jing, Ling Zhen, 2018, Eng. Appl. Artif. Intell..

Novel Grouping Method-based support vector machine plus for structured data

Ling Zhen, Qiuling Hou, Naiyang Deng, 2016, Neurocomputing.

Semi-supervised dimension reduction based on hypergraph embedding for hyperspectral images

Ling Jing, Ling Zhen, Qiuling Hou, 2018 .

Robust weighted linear loss twin multi-class support vector regression for large-scale classification

Jinxin Zhang, Ling Zhen, Wenwen Qiang, 2020, Signal Process..

Sparse least square twin support vector machine with adaptive norm

N. Deng, Junyan Tan, Ling Zhen, 2014, Applied Intelligence.

Support vector machine with hypergraph-based pairwise constraints

Ling Jing, Ling Zhen, Qiuling Hou, 2016, SpringerPlus.

Twin Bounded Support Tensor Machine for Classification

Ling Jing, Ling Zhen, Haifa Shi, 2016, Int. J. Pattern Recognit. Artif. Intell..

Manifold proximal support vector machine with mixed-norm for semi-supervised classification

N. Deng, Junyan Tan, Ling Zhen, 2015, Neural Computing and Applications.

Laplacian p-norm proximal support vector machine for semi-supervised classification

Zhiqiang Zhang, Ling Zhen, Naiyang Deng, 2014, Neurocomputing.

A new support vector machine for the classification of positive and unlabeled examples

Ling Zhen, Nai-Yang Deng, Chunhua Zhang, 2013 .

Manifold proximal support vector machine with mixed-norm for semi-supervised classification

Zhiqiang Zhang, Ling Zhen, Naiyang Deng, 2014, Neural Computing and Applications.

Classification Algorithm Based on Feature Selection and Samples Selection

Ling Zhen, Yitian Xu, Laisheng Wang, 2009, ISNN.