Welcome to our Machine Learning and Data Analysis (MLDA) Lab @ Southwest University! The research interests of MLDA include Machine Learning, Data Mining, Big Data Analysis and Bioinformatics. Our researches are supported by National Natural Science Foundation of China, Technology Foundation for Selected Overseas Chinese Scholars, Natural Science Foundation of Chongqing, and Fundamental Research Funds for the Central Universities.

Recruit Information:
Each faculty in the Lab can recruit and supervise graduate. MLDA always welcome students, who are interested in Machine Learning and Big Data Mining, to join and participate in exciting research topics and to quickly shape yourself. The Lab can provide you with the latest research facilities, timely guidance and various opportunities to co-work with members and collaborators of the MLDA Lab.

Room 1002, 25th Building, College of Computer and Information Science, Southwest University, No. 2 Tiansheng Road, Beibei, Chongqing, China. Zip: 400715, Tel: +86-23-68254396; Email: gxyu@swu.edu.cn


2018-11-01Congratulating on Xing Wang's paper “Multiple Independent Subspace Clusterings”, Yuying Xing's paper "Multi-View Multi-Instance Multi-Label Learning based on Confederate Matrix Factorization" and Xuanwu Liu's paper "Ranking-based Deep Cross-modal Hashing" are accepted by AAAI2019. The overall accept rate is 16.2%=1150/7092
2018-10-11Congratulation, Yuehui Wang's paper "Weighted matrix factorization based data fusion for predicting lncRNA-disease associations" is accepted by BIBM as a regular paper
2018-09-25Congratulations! Ziying Yang's paper "CDPath: Cooperative driver pathways discovery using integer linear programming and Markov clustering" is accepted by APBC
2018-09-06Congratulation! Xing Wang's paper “Network Regularized Bi-Clustering for Cancer Subtype Categorization” is accepted by Chinese Journal of Computer
2018-08-18'Feature-induced Partial Multi-label Learning' 'Cost Effective Multi-label Active Learning via Querying Subexamples' are accepted by ICDM(CCF B) as short paper. Congratulating to Xia Chen !