We construct probabilistic generative models for the non-rigid matching of point-sets. Our formulation is explicitly Platonist. Beginning with a Platonist super point-set, we derive real-world point-sets through the application of four operations: i) spline-based warping, ii) addition of noise, iii) point removal and iii) amnesia regarding the point-to-point correspondences between the real-wor...

In this study we develop pronunciation distances based on naive discriminative learning (NDL). Measures of pronunciation distance are used in several subfields of linguistics, including psycholinguistics, dialectology and typology. In contrast to the commonly used Levenshtein algorithm, NDL is grounded in cognitive theory of competitive reinforcement learning and is able to generate asymmetrica...

The analysis of texture is an important subroutine in application areas as diverse as biology, medicine, robotics and forensic science. While the last three decades have seen extensive research in algorithms to measure texture similarity, almost all existing methods require the careful setting of many parameters. There are many problems associated with a surfeit of parameters, the most obvious ...

In this paper, we explore the problem of classification where class labels exhibit a hierarchical tree structure. Many multiclass classification algorithms assume a flat label space, where hierarchical structures are ignored. We take advantage of hierarchical structures and the interdependencies between labels. In our setting, labels are structured in a product and service hierarchy, with a foc...

In many biological fields (e.g. horticulture, forestry, botany), a need exists to quantify different types of variability within a set of plants. In this paper, we propose a method to compare plant individuals based on a detailed comparison of their architectures. The core of the method relies on an adaptation of an algorithm for comparing rooted tree graphs, recently proposed by Zhang in theor...

In the literature on judgment aggregation, an important open question is how to measure the distance between any two judgment sets. This is relevant for issues of social choice: if two individuals hold different beliefs then we might want to find a compromise that lies somewhere between them. We propose a set of axioms that determine a measure of distance uniquely. This measure differs from the...

The optimal distance measure for a given discrimination task under the nearest neighbor framework has been shown to be the likelihood that a pair of measurements have different class labels [5]. For implementation and efficiency considerations, the optimal distance measure was approximated by combining more elementary distance measures defined on simple feature spaces. In this paper, we address...

In the present paper we shall propose a new measure of the nonclassical distance [1]. The proposed modification is based on the following considerations. If ρ1 and ρ2 are density operators, and F (ρ1, ρ2) is the corresponding fidelity, then from the inequalities [2] 2(1 − √ F (ρ1, ρ2)) ≤ ||ρ1 − ρ2||1 ≤ 2[1− (F (ρ1, ρ2))] 1 2 it is evident that the quantity φ(ρ) = sup ρcl F (ρcl, ρ) can be used ...

Face is considered to be one of the biometrics in automatic person identification. The non-intrusive nature of face recognition makes it an attractive choice. For face recognition system to be practical, it should be robust to variations in illumination, pose and expression as humans recognize faces irrespective of all these variations. In this paper, an attempt to address these issues is made ...

A bottle up hyperbox granular computing (HBGrC) is developed based on distance measure. Firstly, hyperbox granule is represented by the beginning point and the end point. Secondly, the distance measure between two hyperbox granules is defined by the beginning points and the end points. Thirdly, operations between two hyperbox granules are designed to the transformation between two hyperbox gran...