功夫: 2013年8月29日（周四）上午9:30
地址: 耽搁校区 行健楼 1018室
讲座: Big Data Analytics and Non-IIDness Learning
演讲者: 澳大利亚悉尼科技大学 操龙兵 教授
演讲者简介：
操龙兵，澳大利亚悉尼科技大学教授、悉尼科技大学高级分析钻研所创所所长，悉尼科技大学量子推算与智能系统钻研中心数据科学与知识发现尝试室成员；澳洲本钱市场结合钻研中心（CMCRC）数据挖掘方向钻研带头人（Research Leader）。中科院模式鉴别与人为智能博士，悉尼科技大学推算科学博士。IEEE推算机分会和系统、人与节造分会高级会员。IEEE行为与社会信息学工作组主席、IEEE教育数据挖掘工作组主席。IEEE推算机分会和系统、人与节造分会高级会员，多个学术刊物的编委与特刊编纂，PAKDD与ADMA大会主席，ICDM、PAKDD、IAT、ADMA等法式委员会主席或副主席，ICDM、WI/IAT组织委员会主席等，以及蕴含KDD、ICDM、AAMAS等在内的国际会议的法式委员会委员。在数据挖掘与知识发现、行为信息学与行为推算、人为智能与机械进建等领域从事钻研工作，从理论、钻研生造就、实际和贸易项目等方面实现产学研的有效结合。
讲座提要：
Big data is becoming a big thing for theoretical and technical innovation and for bigger business, smarter decisions, and bigger economic and social value. This lecture discusses a recently emerging topic: Non-IIDness Learning, which handles two of fundamental challenges in big data analytics: heterogeneity and couplings. Heterogeneity and couplings in big data fundamentally challenge the classic IIDness foundation in statistics, data mining and machine learning etc. As a result, most of existing algorithms and approaches may not work for big data. On the basis of addressing the limitations of existing IIDness-based analysis, mining and learning, the lecture introduces an extended information table based framework for non-IIDness learning, followed by exemplar techniques and case studies for object and pattern relation analysis, such as coupled clustering, coupled ensemble clustering, coupled behavior analysis, and coupling analysis between textual terms, social media items, and patterns to tackle non-IIDness in big data.
欢迎宽大老师和学生参与！
