Why curriculum learning & self-paced learning work in big/noisy data: A theoretical perspective

Author:

Gong Tieliang,Zhao Qian,Meng Deyu,Xu Zongben

Publisher

American Institute of Mathematical Sciences (AIMS)

Reference23 articles.

1. Teaching Classification Boundaries to Humans,;S. Basu;Proceddings of the 27th AAAI Conference on Artificial Intelligence,2013

2. Curriculum Learning,;Y. Bengio;Proceedings of the 26th International Conference on Machine Learning,2009

3. LIBSVM: A library for support vector machines,;C.-C. Chang;ACM Transactions on Intelligent Systems and Technology,2011

4. NEIL: Extracting visual knowledge from web data,;X. Chen;Proceedings of the IEEE International Conference on Computer Vision,2013

5. On the mathematical foundations of learning,;F. Cucker;Bull. Amer. Math. Soc.,2002

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