Semi-Supervised Learning with Ladder Networks

NeurIPS 2015 Antti RasmusHarri ValpolaMikko HonkalaMathias BerglundTapani Raiko

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... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Semi-Supervised Image Classification CIFAR-10, 4000 Labels Γ-model Accuracy 79.6 # 18

Methods used in the Paper


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