Graph Embedding with Constraints
Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence. Pages 1065-1069.
Abstract
Recently graph based dimensionality reduction has received a lot of interests in many fields of information processing. Central to it is a graph structure which models the geometrical and discriminant structure of the data manifold. When label information is available, it is usually incorporated into the graph structure by modifying the weights between data points. In this paper, we propose a novel dimensionality reduction algorithm, called Constrained Graph Embedding, which considers the label information as additional constraints. Specifically, we constrain the space of the solutions that we explore only to contain embedding results that are consistent with the labels. Experimental results on two real life data sets illustrate the effectiveness of our proposed method.Xiaofei He, Ming Ji, Hujun Bao
@inproceedings{ijcai2009p180,
title = {Graph Embedding with Constraints},
author = {He, Xiaofei and Ji, Ming and Bao, Hujun},
booktitle = {Proceedings of the Twenty-First International Joint Conference on
Artificial Intelligence, {IJCAI-09}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Hiroaki Kitano},
pages = {1065--1069},
year = {2009},
url = {https://ijcai.org/proceedings/2009/180},
}
TY - CPAPER TI - Graph Embedding with Constraints AU - He, Xiaofei AU - Ji, Ming AU - Bao, Hujun T2 - Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence, IJCAI-09 PB - International Joint Conferences on Artificial Intelligence PY - 2009 SP - 1065 EP - 1069 UR - https://ijcai.org/proceedings/2009/180 ER -Copied
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