Naive semi-supervised deep learning using pseudo-label

Author:

Li Zhun,Ko ByungSoo,Choi Ho-Jin

Funder

Korea Meteorological Administration

Korea Electric Power Corporation

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Software

Reference42 articles.

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2. Bachman P, Alsharif O, Precup D (2014) Learning with pseudo-ensembles. In: Advances in neural information processing systems, pp 3365–3373

3. Bengio Y, Lamblin P, Popovici D, Larochelle H (2007) Greedy layer-wise training of deep networks. In: Advances in neural information processing systems, pp 153–160

4. Castelli V, Cover TM (1996) The relative value of labeled and unlabeled samples in pattern recognition with an unknown mixing parameter. IEEE Trans Inf Theory 42(6):2102–2117

5. Chen DD, Wang W, Gao W, Zhou ZH (2018) Tri-net for semi-supervised deep learning. In: Proceedings of the Twenty-Seventh international joint conference on artificial intelligence, IJCAI-18, International Joint Conferences on Artificial Intelligence Organization, pp 2014–2020. https://doi.org/10.24963/ijcai.2018/278

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