[Adapt] [Seminar] An Introduction to Boosting Methods and XGBoost System

Kenny Zhu kzhu at cs.sjtu.edu.cn
Wed Nov 16 21:22:50 CST 2016

Just to remind you: we are meeting in Room 414, not 528 tomorrow.




From: adapt-bounces at cs.sjtu.edu.cn [mailto:adapt-bounces at cs.sjtu.edu.cn] On
Behalf Of Yu Shi
Sent: Wednesday, November 16, 2016 7:48 PM
To: adapt
Subject: [Adapt] [Seminar] An Introduction to Boosting Methods and XGBoost


Dear Adapters,

     Tomorrow I will give an introduction to boosting and XGBoost. Boosting
is one of the most powerful machine learning ideas introduced in the last
twenty years. Though deep learning is quite popular today, boosting still
occupies most top positions on the leader boards of various data mining

     XGBoost is an open source tree boosting system by Tianqi Chen, a former
ACM class member. It is highly efficient and widely used as a machine
learning tool. XGBoost is also an excellent work which combines algorithm
and system design.

     Let's meet at 1:00 p.m. tomorrow (Thursday) at room 3-528.     


Original Paper of XGBoost


XGBoost Website




Yu Shi


Department of Computer Science and Engineering

Shanghai Jiao Tong University

E-mail: shiyu_k1994 at qq.com


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