Learning with Big Data by Incremental Optimization of
Performance Measures
Zhi-Hua Zhou
Nanjing University
Abstract:
A popular approach to achieve a strong learning system is to take the performance
measure that will be used for evaluation as an optimization target, and then accomplish
the learning task by an optimization procedure. Many performance measures in
machine learning, however, are unfortunately non-linear, non-smooth and non-convex,
leading to difficult optimization problems. With big data, the optimization becomes
even more challenging because of the concerns of computational, storage,
communication costs, etc. Particularly, it becomes almost impossible to collect all data
at first and then perform optimization, and it is desired to be able to optimize
performance measures incrementally, without accessing the whole data. In this talk we
will introduce some studies along this direction.
Speaker Biography:
Zhi-Hua Zhou is a Professor and Standing Deputy Director of the National Key Lab for
Novel Software Technology, Nanjing University. His research interests are mainly in
artificial intelligence, machine learning and data mining. He authored the book
"Ensemble Methods: Foundations and Algorithms", and published more than 100
papers in top-tier journals and conference proceedings. According to GoogleScholar,
his papers have received more than 16,000 citations. He also holds 14 patents and has
good experiences in applications. He has received various awards, including the
National Natural Science Award of China, the IEEE CIS Outstanding Early Career
Award, the Microsoft Professorship Award, etc. He serves as the Executive Editor-inChief of Frontiers of Computer Science, Associate Editor-in-Chief of Science China:
Information Science, and Associate Editor of the ACM Trans. IST, IEEE Trans. NNLS,
etc. He is the founder of the ACML (Asian Conference on Machine Learning), Steering
Committee member of PAKDD and PRICAI, and chair of various conferences.
Currently he serves as Advisory Committee member and machine learning track chair
of IJCAI 2015, Program committee chair of ICDM 2015, etc. He is an ACM
Distinguished Scientist, Fellow of the IEEE Fellow, Fellow of the IAPR (International
Association of Pattern Recognition), and Fellow of the CCF (China Computer
Federation).