现在位置:首页 >> 研究队伍 >> 副教授
白亮
副教授,博士,硕士生导师
研究方向:数据挖掘与机器学习
E-Mail:bailiang@sxu.edu.cn
个人简介 科研项目 代表论文
个人简介

白亮,1982年9月生,博士,副教授,硕士生导师。于2012年6月毕业于山西大学计算机与信息技术学院,获博士学位。博士论文《聚类学习的理论分析与高效算法研究》获得了2014届中国人工智能学会优秀博士论文奖和2012届山西省优秀博士论文奖。2010年受香港城市大学制造工程与工程管理系C.Y. Dang教授的邀请,赴香港城市大学进行了为期7个月的学术合作研究。2014年在中科院计算技术研究所进行博士后工作。近年来,一直从事数据挖掘和机器学习领域的学术研究,获得了一系列的创新性的研究成果,发表在国际一流期刊IEEE TPAMI,DMKD, IEEE TFS, INS 和PR等,SCI收录12篇。目前,主持国家自然科学基金(青年)和教育部博士点基金(新教师类)各1项。

科研项目
  1. 山西省研究生优秀创新重点支持项目(No.20103003): 面向分类数据的聚类模型与算法研究, (主持人);
  2. 国家自然科学基金(No.70971080): 面向复杂数据的粗糙集多属性/多准则决策分析研究, 2010.01-2012.12, (参与);
  3. 高等学校博士学科点专项科研基金(No.20101401110002): 基于粒计算的符号数据分析方法研究, 2011.01-2013.12, (参与);
  4. 山西省青年科技基金(No.2010021016-2): 面向符号属性数据的聚类算法研究, 2010.01-2012.12, (参与)。
代表论文
[1]  Liang Bai,Xueqi Cheng,Jiye Liang,Yike Guo. Fast graph clustering with a new description model for community detection, Information Sciences, 2017, 388-389:37–47.
[2]  Liang Bai,Xueqi Chen,Jiye Liang,Huawei Shen,Yike Guo. Fast density clustering strategies based on the k-means algorithm, Pattern Recognition, 2017, 71:375–386.
[3]  杜航远,王文剑,白亮. 一种基于优化模型的演化数据流聚类方法, 中国科学(E辑:信息科学), 2017, 10.1360/N112017-00107.
[4]  Liang Bai,Xueqi Cheng,Jiye Liang,Huawei Shen. An optimization model for clustering categorical data streams with drifting concepts, IEEE Transactions on Knowledge and Data Engineering, 2016, 28(11):2871-2883.
[5]  Liang Bai,Jiye Liang. Cluster validity functions for categorical data:a solution-space perspective, Data Mining and Knowledge Discovery, 2015, 29(6):1560-1597.
[6]  Hangyuan Du,Wenjian Wang,Liang Bai. Observation noise modeling based particle filter: An efficient algorithm for target tracking in glint noise environment, Neurocomputing, 2015, 158:155–166.
[7]  Liang Bai,Jiye Liang. The k-modes type clustering plus between-cluster information for categorical data, Neurocomputing, 2014, 133:111–121.
[8]  Liang Bai,Jiye Liang,Chuangyin Dang,Fuyuan Cao. A novel fuzzy clustering algorithm with between-cluster information for categorical data, Fuzzy Sets and Systems, 2013, 215:55–73.
[9]  Liang Bai,Jiye Liang,Chuangyin Dang,Fuyuan Cao. The impact of cluster representatives on the convergence of the K-Modes type clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6):1509-1522.
[10]  Liang Bai,Jiye Liang,Chao Sui,Chuangyin Dang. Fast global k-means clustering based on local geometrical information, Information Sciences, 2013, 245:168–180.
[11]  Liang Bai,Jiye Liang,Chuangyin Dang,Fuyuan Cao. A cluster centers initialization method for clustering categorical data., Expert Systems with Applications, 2012, 39(9):8022-8029.
[12]  Jiye Liang,Liang Bai,Chuangyin Dang,Fuyuan Cao. The k-means-type algorithms versus imbalanced data distributions, IEEE Transactions on Fuzzy Systems, 2012, 20(4):728-745.
[13]  Fuyuan Cao,Jiye Liang,Deyu Li,Liang Bai,Chuangyin Dang. A dissimilarity measure for the k-Modes clustering algorithm, Knowledge-Based Systems, 2012, 26:120-127.
[14]  Liang Bai,Jiye Liang,Chuangyin Dang,Fuyuan Cao. A novel attribute weighting algorithm for clustering high-dimensional categorical data, Pattern Recognition, 2011, 44(12):2843-2861.
[15]  Liang Bai,Jiye Liang,Chuangyin Dang. An initialization method to simultaneously find initial cluster centers and the number of clusters for clustering categorical data, Knowledge-Based Systems, 2011, 24(6):785-795.
[16]  梁吉业,白亮,曹付元. 基于新的距离度量的K-Modes聚类算法, 计算机研究与发展, 2010, 47(10):1749-1755.
[17]  Fuyuan Cao,Jiye Liang,Liang Bai,Xingwang Zhao,Chuangyin Dang. A framework for clustering categorical time-evolving data, IEEE Transactions on Fuzzy Systems, 2010, 18(5):872-882.
[18]  Fuyuan Cao,Jiye Liang,Liang Bai. A new initialization method for categorical data clustering, Expert Systems with Applications, 2009, 36(7):10223-10228.