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Research

Machine Learning and Pattern Recognition Team

Approval Year: 2016

Leader: Ming Yang

Members: Jianhua Xu, Weiling Cai, Fengyi Song, Jing Lv, Guihua Xing, Aibin Zheng, Wanqi Yang

 

Introduction

The group of “Machine Learning and Pattern Recognition” mainly concentrates the study of making machines capable of acquiring knowledge from observations and generalizing to unseen cases. This study relates to machine learning, data mining, pattern recognition, artificial intelligence, and computer vision, etc. This group consists of 2 professors, 2 associate professors, and 4 lecturers. In the recent 5 year, this group published more than 80 papers (more than 20 papers were published in SCI journals); more than 2 invention patents have been authorized; and more than 6 NSFC projects have been granted.

 

Research Contents

Online learning for big data

Cost-sensitive and class-imbalance learning

Dimensionality Reduction and feature selection

Sparse representation and learning

Structure learning and clustering analysis

Multi-label learning and Attribute learning

Zero-shot learning

Image processing and understanding

 

Representative Achievements

  1.  J. W. Wan, M. Yang*, Y. Gao, Y. J. Chen. Pairwise Costs in Semisupervised Discriminant Analysis for Face Recognition. IEEE Transaction on Information forensics and Security, 2014,9(10): 569-1580.
  2. H. D. Liu, M. Yang*, Y. Gao, L.B. Cao. Fast Local Histogram Specification. IEEE Transaction on Circuts and Systems for Video technology, 2014,24(11): 1833-1843.
  3. W. Q. Yang, Y. Gao, Y. H. Shi, L. B. Cao. MRM-Lasso: A Sparse Multi-view Feature Selection Method via Low-Rank Analysis, IEEE Trans. Neural Networks and learning systems, 2015,26(11), 2801-2815.
  4. W. L. Cai, S. C. Chen and D. Q. Zhang. A Multi-objective Simultaneous Learning Framework for Clustering and Classification, IEEE Trans. Neural Networks, 2010,21(2):185-200.
  5. H. D. Liu, M.Yang*, Y. Gao, Y. L.Yin. Bilinear Discriminative Dictionary Learning for Face Recognition. Pattern Recognition, 2014,47(5): 1835-1845.
  6. J. H. Xu. Fast multi-label core vector machine. Pattern Recognition, 2013, 46(3): 885-898.
  7. J. H. Xu. Multi-label core vector machine with a zero label.Pattern Recognition, 2014, 47(7):2542-2557
  8. F. Song, X. Tan*,X. Liu, S. Chen, Eyes closeness detection from still images with multi-scale histograms of principal oriented gradients,Pattern Recognition, 2014,47(9): 2825-2838.
  9. W. L. Cai, S. C. Chen and D. Q. Zhang. A Simultaneous Learning Framework for Clustering and Classification, Pattern Recognition, 2009,42(7): 1248-1259, 2009.

 

Research Projects 

 

Title

Leader

Type

Period

The theory and Applications in Big Data Oriented Knowledge Representation, Reasoning, and Online Learning

Ming Yang

Key project National Natural Science Foundation of China

from 2015-1 to 2019-12

Research on machine learning technology aiming at multiple costs imbalance

Ming Yang

National Natural Science Foundation of China

from 2013-1 to 2016-12

Research on Feature Extraction and Selection Algorithm in Multi-label classification

Jianhua Xu

National Natural Science Foundation of China

from 2013-1 to 2016-12

Research on Online Clustering Learning and its Extension for Multi-view Data

 

Weiling Cai

Natural Science Foundation of Jiangsu Province

from 2016-7 to 2019-7

Research on Face Attribute Learning under Uncontrolled Conditions

Fengyi Song

Natural Science Foundation of Jiangsu Province

from 2016-7 to 2019-7

Massive data processing and analysis for the Internet of Things and cloud computing environment

Ming Yang

Key project National Natural Science Foundation of Jiangsu Province

from 2011.7  to 2014.12

 

Research Achievements 

 

Program Title

Type

Grade

Year

Program Units

Program Members

Development and application of outpatient medical information intelligent fusion and automatic triage guiding system

Science and Technology Award of Jiangsu Province

 

Third Prize

2015

People's Government of Jiangsu Province

 

Ming Yang

Fast and Robust Fuzzy c-means Clustering Algorithms Incorporating Local Information for Image Segmentation

Outstanding Paper Award of Honorable Mentions

 

2009

SCI Journal  Pattern Recognition

 

Weiling Cai