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Exemplar learning is a powerful paradigm for discovering visual similarities in an unsupervised manner.
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Online multiple kernel similarity learning for visual search
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Per-sample kernel adaptation for visual recognition and grouping
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Regularizing max-margin exemplars by reconstruction and generative models
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Unsupervised learning of visual representations using videos
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