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 ...

This paper presents a new and efficient approach for metric learning in latent space. Our method discovers an optimal mapping from the feature space to a latent space that shrinks the distance between similar data items ...

over the last few years, manifold clustering has attracted considerable interest in high-dimensional data clustering. However achieving accurate clustering results that match user desires and data structure is still an ...