Nearest neighbor-based techniques provide an approach to acoustic modeling that avoids the often lengthy and heuristic process of training traditional Gaussian mixturebased models. Here we study the problem of choosing the distance metric for a k-nearest neighbor (k-NN) phonetic frame classifier. We compare the standard Euclidean distance to two learned Mahalanobis distances, based on large-mar...

Statistical learning algorithms often rely on the Euclidean distance. In practice, non-Euclidean or non-metric dissimilarity measures may arise when contours, spectra or shapes are compared by edit distances or as a consequence of robust object matching [1,2]. It is an open issue whether such measures are advantageous for statistical learning or whether they should be constrained to obey the me...

The vast number of applications featuring multimedia and geometric data has made the R-tree a ubiquitous data structure in databases. A popular and fundamental operation on R-trees is nearest neighbor search. While nearest neighbor on R-trees has received considerable experimental attention, it has received somewhat less theoretical consideration. We study pruning heuristics for nearest neighbo...

This paper examines the relationship between road directions and the rectilinear distance in regular point patterns. We derive the distributions of the rectilinear distances to the nearest and the second nearest points in rotated regular point patterns. These distributions demonstrate that road directions significantly affect the rectilinear distances. As an application of the nearest and the s...

Distance FromHome to theNearest TobaccoOutlet MayNot Reflect the True Accessibility To the Editor In their Original Investigation in a recent issue of JAMA InternalMedicine, Pulakka et al1 examined the association between walking distance from home to the nearest tobacco outlet and smoking cessation and relapse. We noticed several limitations that should be considered. First, Pulakka et al1 sim...

Spectral clustering is a method of subspace clustering which is suitable for the data of any shape and converges to global optimal solution. By combining concepts of shared nearest neighbors and geodesic distance with spectral clustering, a self-adaptive spectral clustering based on geodesic distance and shared nearest neighbors was proposed. Experiments show that the improved spectral clusteri...

We develop a multi-class object detection framework whose core component is a nearest neighbor search over object part classes. The performance of the overall system is critically dependent on the distance measure used in the nearest neighbor search. A distance measure that minimizes the mis-classification risk for the 1-nearest neighbor search can be shown to be the probability that a pair of ...

This paper describes the participation of smallholders in commercial horticultural farming in Kenya and identifies constraints and critical factors that influence their decision to participate in this industry by selling their produce. The study employs panel survey data on smallholder producers of both international (export) and domestic market vegetables and controls for unobserved heterogene...

The main goal of the present study was to implement a hybrid pattern of cellular automata model and particle swarm optimization algorithm based on TM and ETM+ imagery of landsat satellite from 1988 to 2010 for simulating the urban sprawling. In this study, an alternative model was implemented in two ways: the first method was based on two images (1988 and 2010) and the second one was based on t...

Rhizoma Menispermi, derived from the rhizoma of Menispermum dauricum DC., is one of the most popular Chinese medicines. However Rhizoma Menispermi is often illegally mixed with other species in the herbal market, including Aristolochia mollissimae Hance, which is toxic to the kidneys and potentially carcinogenic. The use of DNA barcoding to authenticate herbs has improved the management and saf...