Support Vector Machines represent a new approach to pattern classification developed from the theory of Structural Risk Minimization[1]. In this paper, we present an investigation into the application of Support Vector Machines’ to the confidence measurement problem in speech recognition. Specifically, based on the results from an initial decoding of an utterance during speech recognition, we d...

Motivation: The advent of new genomic technologies has resulted in the production of massive data sets. Analyses of these data require new statistical and computational methods. In this article, we propose one such method that is useful in selecting explanatory variables for prediction of a binary response. Although this problem has recently been addressed using penalized likelihood methods, we...

Nearly all cellular processes involve proteins structurally rearranging to accommodate molecular partners. The energy landscape underscores the inherent nature of proteins as dynamic molecules interconverting between structures with varying energies. Reconstructing a protein’s energy landscape holds the key to characterizing the structural dynamics and its regulation of protein function. In pra...

Recent scientific and technological advances have witnessed an abundance of structural patterns modeled as graphs. As a result, it is of special interest to process graph containment queries effectively on large graph databases. Given a graph database G, and a query graph q, the graph containment query is to retrieve all graphs in G which contain q as subgraph(s). Due to the vast number of grap...

Graph-based representations are of broad use and applicability in pattern recognition. They exhibit, however, a major drawback with regards to the processing tools that are available in their domain. Graph embedding into vector spaces is a growing field among the structural pattern recognition community which aims at providing a feature vector representation for every graph, and thus enables cl...

Automatic machine-printed Optical Characters or texts Recognizers (OCR) are highly desirable for a multitude of modern IT applications, including Digital Library software. However, the state of the art OCR systems cannot do for Myanmar scripts as the language poses many challenges for document understanding. Therefore, the authors design an Optical Character Recognition System for Myanmar Print...

This paper discusses structural risk minimization in the setting of classification with a reject option. Binary classification is about classifying observations that take values in an arbitrary feature space X into one of two classes, labelled −1 or +1. A discriminant function f : X → R yields a classifier sgn(f(x)) ∈ {−1,+1} that represents our guess of the label Y of a future observation X an...

Music structural segmentation (MSS) studies to date mainly employ audio features describing the timbral, harmonic or rhythmic aspects of the music and are evaluated using datasets consisting primarily of Western music. A new dataset of Chinese traditional Jingju music with structural annotations is introduced in this paper to complement the existing evaluation framework. We discuss some statist...

In this paper, we study the performance of the feature extraction method we developed for complex object databases, called Complex Object Feature Extraction (Cofe), with respect to protein datasets, using distance measures based on structural similarity between proteins. We rst perform an assessment of the accuracy of six automatic protein comparison methods against the manually constructed cla...

BACKGROUND: Timing properties are hard to specify, and even harder to analyse as interactions may arise from multiple independent properties. OBJECTIVE: We introduce the notion of timing feature interaction (TFI), and show how to automatically detect many TFIs. METHOD: We identify common structural patterns of timing specifications and show how they can be translated into UML 2 interactions wit...