讲座题目：MASCOT: Fast and Highly Scalable SVM Cross-validation using GPUs and SSDs
Associate Professor and Reader at Department of Computing and Information Systems
Assistant Dean (Collaboration) of Melbourne School of Engineering
The University of Melbourne
Cross-validation is a commonly used method for evaluating the effectiveness of Support Vector Machines (SVMs). However, existing SVM cross-validation algorithms are not scalable to large datasets. In this work, we propose a scheme to dramatically improve the scalability and efficiency of SVM cross-validation. For the tested datasets of sizes that existing algorithms can handle, our scheme achieves several orders of magnitude of speedup. More importantly, our scheme enables SVM cross-validation on datasets of very large scale that existing algorithms are unable to handle.
Rui Zhang is an Associate Professor and Reader at the University of Melbourne and Assistant Dean (Collaboration) of Melbourne School of Engineering. He has been awarded the Future Fellowship by the Australian Research Council in 2012. He obtained his Bachelor's degree from Tsinghua University in 2001 and PhD from National University of Singapore in 2006. He has been a visiting scholar in AT&T Labs-Research and Microsoft Research before and is now a regular visiting researcher at Microsoft Research Asia in Beijing. He has authored 70 publications in prestigious conferences and journals. His research interest is spatial and temporal data analytics, as well as general database and mining techniques including indexing, moving object management, data streams and sequence databases. He regularly serves as PC members of top conferences in data management and mining such as SIGMOD, VLDB, ICDE and KDD. He is an associate editor of Distributed and Parallel Databases. 应计算机学院智能与分布计算实验室邀请，澳大利亚墨尔本大学张瑞副教授将于2014年12月25日（周四）上午来计算机学院举行学术报告，欢迎广大师生参加。