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A major challenge in similarity/distance learning is attaining a strong measure which is close to human notions of similarity. This paper shows why the consideration of data distribution can yield a more effective similarity measure. In addition, the current work both introduces a new scalable similarity measure based on the posterior distribution of data and develops a practical algorithm that learns...
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