Semi-Supervised Learning with Ladder Networks

Antti Rasmus

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Mathias Berglund

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Mikko Honkala

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Harri Valpola

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Tapani Raiko

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Annual Conference on Neural Information Processing Systems, pp. 3546-3554, 2015.

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Keywords:

convolutional neural networksmulti-layer perceptronsMulti-prediction deep Boltzmann machinestacked what-where autoencoderladder networkMore(15+)

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We showed how a simultaneous unsupervised learning task improves convolutional neural networks and multi-layer perceptrons networks reaching the state-of-the-art in various semi-supervised learning tasks

Abstract:

We combine supervised learning with unsupervised learning in deep neural networks. The proposed model is trained to simultaneously minimize the sum of supervised and unsupervised cost functions by backpropagation, avoiding the need for layer-wise pre-training. Our work builds on top of the Ladder network proposed by Valpola [1] which we e...More

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