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Towards Self-Adaptive Metric Learning On the Fly
In this paper, we present a new online metric learning framework that attempts to tackle the challenge by learning an ANN-based metric with adaptive model complexity from a stream of constraints.
Co-Representation Learning For Classification and Novel Class Detection via Deep Networks
In this paper, we address this key challenge by proposing a semi-supervised multi-task learning framework called \sysname{} which aims to intrinsically search for a latent space suitable for detecting labels of instances from both known and unknown classes.
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