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Unsupervised Estimation of Ensemble Accuracy
Ensemble learning combines several individual models to obtain a better generalization performance.
Learning a Metric Embedding for Face Recognition using the Multibatch Method
This work is motivated by the engineering task of achieving a near state-of-the-art face recognition on a minimal computing budget running on an embedded system.
Minimizing the Maximal Loss: How and Why?
Second, it is often argued that there is no sense to minimize the loss on the training set too much, as it will not be reflected in the generalization loss.
ShareBoost: Efficient multiclass learning with feature sharing
We consider the problem of learning a multiclass predictor that uses only few features, and in particular, the number of used features should increase sub-linearly with the number of possible classes.
