Distributed representation learning with skip-gram model for trained random forests

Author:

Ma Chao,Wang Tianjun,Zhang Le,Cao Zhiguang,Huang Yue,Ding Xinghao

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference43 articles.

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2. S. Bengio, J. Weston, D. Grangier, Label embedding trees for large multi-class tasks. In Proceedings of the 23rd International Conference on Neural Information Processing Systems-Volume 1, 163–171, 2010.

3. Representation learning: A review and new perspectives;Bengio;IEEE Trans. Pattern Anal. Mach. Intell.,2013

4. A comprehensive survey of graph embedding: Problems, techniques, and applications;Cai;IEEE Transa. Knowl. Data Eng.,2018

5. J. Feng, Z.-H. Zhou, Autoencoder by forest. In Proceedings of the AAAI conference on artificial intelligence, volume 32, 2018.

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