This article presents a derivation of a new relative fractal dimension spectrum, DRq, to measure the dis-similarity between two finite probability distributions originating from various signals. This measure is an extension of the Kullback-Leibler (KL) distance and the Rényi fractal dimension spectrum, Dq. Like the KL distance, DRq determines the dissimilarity between two probability distibutio...

Supervised learning has been very successful for automatic segmentation of images from a single scanner. However, several papers report deteriorated performances when using classifiers trained on images from one scanner to segment images from other scanners. We propose a transfer learning classifier that adapts to differences between training and test images. This method uses a weighted ensembl...

Clustering short length texts is a difficult task itself, but adding the narrow domain characteristic poses an additional challenge for current clustering methods. We addressed this problem with the use of a new measure of distance between documents which is based on the symmetric Kullback-Leibler distance. Although this measure is commonly used to calculate a distance between two probability d...

This paper describes the approach of the Hochschule Hannover to the SemEval 2013 Task Evaluating Phrasal Semantics. In order to compare a single word with a two word phrase we compute various distributional similarities, among which a new similarity measure, based on Jensen-Shannon Divergence with a correction for frequency effects. The classification is done by a support vector machine that us...

Vulnerabilities in biometric systems including spoofing has emerged as an important issue. The focus of this work is on characterization of ‘perspiration pattern’ in a time-series of fingerprint images for liveness detection. By using information in the high pass bands of the images the similarity score for the two images is calculated to determine the uniqueness of the perspiration pattern. In...

Bound entangled states are states that are entangled but from which no entanglement can be distilled if all parties are allowed only local operations and classical communication. However, in creating these states one needs nonzero entanglement resources to start with. Here, the entanglement of two distinct multipartite bound entangled states is determined analytically in terms of a geometric me...

In this paper, we present a data-driven approach for challenge 1 of the MediaEval 2013 Social Event Detection Task. Our proposed approach consists of the following steps: (a) initialization based on the images’ spatio-temporal information; (b) computation of clusters’ intercorrelations; and (c) the final clusters’ generation. In the initialization step, the images that have both geolocation and...

Active selection of good training examples is an important approach to reducing data-collection costs in machine learning; however, most existing methods focus on maximizing classification accuracy. In many applications, such as those with unequal misclassification costs, producing good class probability estimates (CPEs) is more important than optimizing classification accuracy. We introduce no...

Let f : (0, ∞) → R be a convex function with f (1) = 0. By virtue of convexity, both the limits f (0) := lim x↓0 f (x) and f (∞) := lim x↑∞ f (x)/x exist, although they may be equal to +∞. For two probability measures P and Q, the f-divergence D f (P ||Q) is defined by D f (P ||Q) := {q > 0} f p q dQ + f (∞)P {q = 0} , where p and q denote the densities of P and Q with respect to a common measu...

The information divergence of a probability measure P from an exponential family E over a nite set is de ned as in mum of the divergences of P from Q subject to Q ∈ E . All directional derivatives of the divergence from E are explicitly found. To this end, behaviour of the conjugate of a log-Laplace transform on the boundary of its domain is analysed. The rst order conditions for P to be a maxi...