报告题目:Leveraging in Big Data Regression报告人:佐治亚大学统计系马平教授
报告地点:十大澳门信誉老牌网赌本部主教108
报告时间:5月21日下午14:00
报告摘要:
Advances in science and technology in the past a few decades have led to big data explosion across a variety of fields. Extraction of useful information and knowledge from big data is a grand challenge. To tackle this challenge requires major breakthroughs in efficient computational and statistical approaches to big data analytics.
In this talk, I will present some leveraging algorithms, which make a key contribution to resolving the grand challenge. In these algorithms, by sampling a very small representative sub-dataset using smart algorithms, one can effectively extract relevant information of vast data sets from the small sub-dataset. Such algorithms are scalable to big data. These efforts allow pervasive access to big data analytics especially for those who cannot directly use supercomputers. More importantly, these algorithms enable massive ordinary users to analyze big data using tablet computers.
报告人简介:
马平教授1996年毕业于南开大学,获金融数学学士学位;2003年获普渡大学统计学博士学位;2003年至2005年在哈佛大学统计系从事博士后研究。2005年至2013年,就职于伊利诺伊大学香槟分校(UIUC)统计系,历任助理教授、副教授;2013年秋,加入佐治亚大学(UGA)统计系,担任副教授至今。马平教授在非参数统计、数据建模、超大样本统计等方面有着很深的理论造诣,在生物信息、地球物理等应用方向做出了一系列重要工作。在高水平学术杂志上发表论文20余篇,承担9项美国国家科学基金(NSF)科研项目。