User talk:Xxiong

Team Members

Xuehan Xiong [xxiong@andrew.cmu.edu]

Goal

1. A revisit of boosting. 2.

Motivation

1. In the traditional boosting, within each iteration the mis-classified samples are weighted more in the next round. However, these errors are made from training data. In my algorithm, I will give more weight to the data that are mis-labeled from cross-validation process, as in stacking.

2.

What question you want to answer

1. I want to know whether the proposed algorithm will outperform the traditional Ada-boost.

2.

Experience with CRF and stacking in the domain of computer vision.