Wootters? distance revisited: a new distinguishability criterium

The normalized compression distance and image distinguishability

We use an information-theoretic distortion measure called the Normalized Compression Distance (NCD), first proposed by M. Li et al., to determine whether two rectangular gray-scale images are visually distinguishable to a human observer. Image distinguishability is a fundamental constraint on operations carried out by all players in an image watermarking system. The NCD between two binary strin...

Orientation distance graphs revisited

The orientation distance graph Do(G) of a graph G is defined as the graph whose vertex set is the pair-wise non-isomorphic orientations of G, and two orientations are adjacent iff the reversal of one edge in one orientation produces the other. Orientation distance graphs was introduced by Chartrand et al. in 2001. We provide new results about orientation distance graphs and simpler proofs to ex...

Distance Metric Learning Revisited

The success of many machine learning algorithms (e.g. the nearest neighborhood classification and k-means clustering) depends on the representation of the data as elements in a metric space. Learning an appropriate distance metric from data is usually superior to the default Euclidean distance. In this paper, we revisit the original model proposed by Xing et al. [24] and propose a general formu...

Approximate Distance Oracles Revisited

Let G be a geometric t-spanner in E with n vertices and m edges, where t is a constant. We show that G can be preprocessed in O(m log n) time, such that (1 + ")-approximate shortest-path queries in G can be answered in O(1) time. The data structure uses O(n log n) space.

Some properties of a new fuzzy distance measure