Abs: In this talk, we will present gcForest, a decision tree ensemble approach with performance highly competitive to deep neural networks in a broad range of tasks. In contrast to deep neural networks which require great effort in hyper-parameter tuning, gcForest is much easier to train; even when it is applied to different data across different domains in our experiments, excellent performance can be achieved by almost same settings of hyper-parameters.

Bio: Zhi-Hua Zhou is a Professor and Founding Director of the LAMDA Group at Nanjing University. His main research interests are in artificial intelligence, machine learning and data mining. He authored the books "Ensemble Methods: Foundations and Algorithms" and "Machine Learning (in Chinese)", and published more than 200 papers in top-tier international journals/conferences. According to Google Scholar, his publications have received more than 30,000 citations, with an H-index of 82. He also holds 22 patents and has good experiences in industrial applications. He has received various awards, including the National Natural Science Award of China, PAKDD Distinguished Contribution Award, IEEE ICDM Outstanding Service Award, Microsoft Professorship Award, etc. He serves as the Executive Editor-in-Chief of Frontiers of Computer Science, Associate Editor-in-Chief of Science China: Information Science, and Associate Editor of IEEE Trans Pattern Analysis and Machine Intelligence, ACM Trans Knowledge Discovery from Data, etc. He founded ACML (Asian Conference on Machine Learning) and served as General co-chair of IEEE ICDM 2016, Program co-chair of IJCAI 2015 Machine Learning track, etc. He will serve as Program co-chair of AAAI 2019. He also serves as the Chair of the CCF-AI, and was Chair of the IEEE CIS Data Mining Technical Committee. He is a foreign member of the Academy of Europe, and Fellow of the ACM, AAAI, AAAS, IEEE, IAPR and CCF. URL: http://cs.nju.edu.cn/zhouzh/