Dynamics of on-line learning in radial basis function networks

On-line learning is examined for the radial basis function network, an important and practical type of neural network. The evolution of generalization error is calculated within a framework which allows the phenomena of the learning process, such as the specialization of the hidden units, to be analyzed. The distinct stages of training are elucidated, and the role of the learning rate described. The three most important stages of training, the symmetric phase, the symmetry-breaking phase, and the convergence phase, are analyzed in detail; the convergence phase analysis allows derivation of maximal and optimal learning rates. As well as finding the evolution of the mean system parameters, the variances of these parameters are derived and shown to be typically small. Finally, the analytic results are strongly confirmed by simulations.

On-line learning with adaptive back-propagation in two-layer networks

An adaptive back-propagation algorithm parameterized by an inverse temperature 1/T is studied and compared with gradient descent (standard back-propagation) for on-line learning in two-layer neural networks with an arbitrary number of hidden units. Within a statistical mechanics framework, we analyse these learning algorithms in both the symmetric and the convergence phase for finite learning rates in the case of uncorrelated teachers of similar but arbitrary length T. These analyses show that adaptive back-propagation results generally in faster training by breaking the symmetry between hidden units more efficiently and by providing faster convergence to optimal generalization than gradient descent.

Transients and asymptotics of natural gradient learning

We analyse natural gradient learning in a two-layer feed-forward neural network using a statistical mechanics framework which is appropriate for large input dimension. We find significant improvement over standard gradient descent in both the transient and asymptotic phases of learning.

Globally optimal on-line learning rules

We present a method for determining the globally optimal on-line learning rule for a soft committee machine under a statistical mechanics framework. This work complements previous results on locally optimal rules, where only the rate of change in generalization error was considered. We maximize the total reduction in generalization error over the whole learning process and show how the resulting rule can significantly outperform the locally optimal rule.

On-line learning of unrealizable tasks

The dynamics of on-line learning is investigated for structurally unrealizable tasks in the context of two-layer neural networks with an arbitrary number of hidden neurons. Within a statistical mechanics framework, a closed set of differential equations describing the learning dynamics can be derived, for the general case of unrealizable isotropic tasks. In the asymptotic regime one can solve the dynamics analytically in the limit of large number of hidden neurons, providing an analytical expression for the residual generalization error, the optimal and critical asymptotic training parameters, and the corresponding prefactor of the generalization error decay.

The theory of on-line learning: a statistical physics approach

In this paper we review recent theoretical approaches for analysing the dynamics of on-line learning in multilayer neural networks using methods adopted from statistical physics. The analysis is based on monitoring a set of macroscopic variables from which the generalisation error can be calculated. A closed set of dynamical equations for the macroscopic variables is derived analytically and solved numerically. The theoretical framework is then employed for defining optimal learning parameters and for analysing the incorporation of second order information into the learning process using natural gradient descent and matrix-momentum based methods. We will also briefly explain an extension of the original framework for analysing the case where training examples are sampled with repetition.

Innovation management using logical framework in hospital-based healthcare units

Innovation is part and parcel of any service in today's environment, so as to remain competitive. Quality improvement in healthcare services is a complex, multi-dimensional task. This study proposes innovation management in healthcare services using a logical framework. A problem tree and an objective tree are developed to identify and mitigate issues and concerns. A logical framework is formulated to develop a plan for implementation and monitoring strategies, potentially creating an environment for continuous quality improvement in a specific unit. We recommend logical framework as a valuable model for innovation management in healthcare services. Copyright © 2006 Inderscience Enterprises Ltd.

Towards an inter-organisational knowledge transfer framework for SMEs

This paper aims to develop a framework for SMEs to help them understand, and thus to improve, the process of knowledge exchange with their customers or suppliers. Through a review of the literature on knowledge transfer, organisational learning, social network theory and electronic networks, the key actors, key factors and their relationships in the process are identified. Finally, a framework containing all above points is proposed.

Cohesion or confusion? Towards a typology for organizational learning research

The study of organizational learning is no longer in its infancy. Since Cyert and March first introduced the notion in the early 1960s, a plethora of books and journal publications have presented their own interpretations of the meaning and significance of the term. Despite such endeavours, there is little common agreement about what organizational learning represents and how future research may build cumulatively upon the many diverse ideas articulated. The intention here is by no means to address these issues, which have been comprehensively examined elsewhere. The purpose is rather to compare and contrast approaches in order to analyse similarities and dissimilarities, together with research challenges, for each approach. This is achieved by presenting a comparative framework to categorize the literature according to (a) its prescriptive/explanatory bias and (b) in line with the level of analysis, examining whether there is a focus on the organization as a whole or upon individuals and their work communities instead. The review concludes by presenting some preliminary suggestions for cross-quadrant research. © Blackwell Publishing Ltd 2006.

Visual data mining: integrating machine learning with information visualization

Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. Most existing systems concentrate either on mining algorithms or on visualization techniques. Though visual methods developed in information visualization have been helpful, for improved understanding of a complex large high-dimensional dataset, there is a need for an effective projection of such a dataset onto a lower-dimension (2D or 3D) manifold. This paper introduces a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualization domain. The framework follows Shneiderman’s mantra to provide an effective user interface. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection methods, such as Generative Topographic Mapping (GTM) and Hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, billboarding, and user interaction facilities, to provide an integrated visual data mining framework. Results on a real life high-dimensional dataset from the chemoinformatics domain are also reported and discussed. Projection results of GTM are analytically compared with the projection results from other traditional projection methods, and it is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework.

Supply chain performance measurement framework:case studies on the Thai manufacturers

One of the most significant paradigm shifts of modern business management is that individual businesses no longer compete as solely autonomous entities, but rather as supply chains. Firms worldwide have embraced the concept of supply chain management as important and sometimes critical to their business. The idea of a collaborative supply chain is to gain a competitive advantage by improving overall performance through measuring a holistic perspective of the supply chain. However, contemporary performance measurement theory is somewhat fragmented and fails to support this idea. Therefore, this research develops and applies an integrated supply chain performance measurement framework that provides a more holistic approach to the study of supply chain performance measurement by combining both supply chain macro processes and decision making levels. Therefore, the proposed framework can provide a balanced horizontal (cross-process) and vertical (hierarchical decision) view and measure the performance of the entire supply chain system. Firstly, literature on performance measurement frameworks and performance measurement factors of supply chain management will help to develop a conceptual framework. Next the proposed framework will be presented. The framework will be validated through in-depth interviews with three Thai manufacturing companies. The fieldwork combined varied sources in order to understand the views of manufacturers on supply chain performance in the three case study companies. The collected data were analyzed, interpreted, and reported using thematic analysis and analysis hierarchy process (AHP), which was influenced by the study’s conceptual framework. This research contributes a new theory of supply chain performance measurement and knowledge on supply chain characteristics of a developing country, Thailand. The research also affects organisations by preparing decision makers to make strategic, tactical and operational level decisions with respect to supply chain macro processes. The results from the case studies also indicate the similarities and differences in their supply chain performance. Furthermore, the implications of the study are offered for both academic and practical use.

A composite framework for the strategic alignment of information systems development

Information systems are corporate resources, therefore information systems development must be aligned with corporate strategy. This thesis proposes that effective strategic alignment of information systems requires information systems development, information systems planning and strategic management to be united. Literature in these areas is examined, breaching the academic boundaries which separate these areas, to contribute a synthesised approach to the strategic alignment of information systems development. Previous work in information systems planning has extended information systems development techniques, such as data modelling, into strategic planning activities, neglecting techniques of strategic management. Examination of strategic management in this thesis, identifies parallel trends in strategic management and information systems development; the premises of the learning school of strategic management are similar to those of soft systems approaches to information systems development. It is therefore proposed that strategic management can be supported by a soft systems approach. Strategic management tools and techniques frame individual views of a strategic situation; soft systems approaches can integrate these diverse views to explore the internal and external environments of an organisation. The information derived from strategic analysis justifies the need for an information system and provides a starting point for information systems development. This is demonstrated by a composite framework which enables each information system to be justified according to its direct contribution to corporate strategy. The proposed framework was developed through action research conducted in a number of organisations of varying types. This suggests that the framework can be widely used to support the strategic alignment of information systems development, thereby contributing to organisational success.

Moving from HRM to knowledge productivity:a study of whether and how organizations become learning organizations

Practitioners and academics are in broad agreement that, above all, organizations need to be able to learn, to innovate and to question existing ways of working. This thesis develops a model to take into account, firstly, what determines whether or not organizations endorse practices designed to facilitate learning. Secondly, the model evaluates the impact of such practices upon organizational outcomes, measured in terms of products and technological innovation. Researchers have noted that organizations that are committed to producing innovation show great resilience in dealing with adverse business conditions (e.g. Pavitt, 1991; Leonard Barton, 1998). In effect, such organizations bear many of the characteristics associated with the achievement of ‘learning organization’ status (Garvin, 1993; Pedler, Burgoyne & Boydell, 1999; Senge, 1990). Seven studies are presented to support this theoretical framework. The first empirical study explores the antecedents to effective learning. The three following studies present data to suggest that people management practices are highly significant in determining whether or not organizations are able to produce sustained innovation. The thesis goes on to explore the relationship between organizational-level job satisfaction, learning and innovation, and provides evidence to suggest that there is a strong, positive relationship between these variables. The final two chapters analyze learning and innovation within two similar manufacturing organizations. One manifests relatively low levels of innovation whilst the other is generally considered to be outstandingly innovative. I present the comparative framework for exploring the different approaches to learning manifested by the two organizations. The thesis concludes by assessing the extent to which the theoretical model presented in the second chapter is borne out by the findings of the study. Whilst this is a relatively new field of inquiry, findings reveal that organizations have a much stronger chance of producing sustained innovation where they manage people proactively where people process themselves to be satisfied at work. Few studies to date have presented empirical evidence to substantiate theoretical endorsements to engage in higher order learning, so this research makes an important contribution to existing literature in this field.

A study in Britain and France of the development of cross-cultural in-house sales training using distance learning.

The thesis is concerned with cross-cultural distance learning in two countries: Great Britain and France. Taking the example of in-house sales training, it argues that it is possible to develop courses for use in two or more countries of differing culture and language. Two courses were developed by the researcher. Both were essentially print-based distance-learning courses designed to help salespeople achieve a better understanding of their customers. One used a quantitative, the other qualitative approach. One considered the concept of the return on investment and the other, for which a video support was also developed, considered the analysis of a customer's needs. Part 1 of the thesis considers differences in the training context between France and Britain followed by a review of the learning process with reference to distance learning. Part 2 looks at the choice of training medium course design and evaluation and sets out the methodology adopted, including problems encountered in this type of fieldwork. Part 3 analyses the data and draws conclusions from the findings, before offering a series of guidelines for those concerned with the development of cross-cultural in-house training courses. The results of the field tests on the two courses were analysed in relation to the socio-cultural, educational and experiential background of the learners as well as their preferred learning styles. The thesis argues that it is possible to develop effective in-house sales training courses to be used in two cultures and identifies key considerations which need to be taken into account when carrying out this type of work.

A prediction of outcomes: a psychological investigation into cognitive and affective development within the framework of adult literacy provision

This investigation seeks to explore the hypothesis, derived from observation and practice, that there is a strong relationship between the development of literacy skills and the growth of confidence in adult literacy students. Implicit in the developmental approach is the notion of progression towards some cognitive goal. Such a goal necessitates the establishment of a base line of existing attainment, together with subsequent assessment so that progress and development can be measured. The study includes an evaluation of existing formal and informal methods of initial and subsequent assessment and diagnosis available at the time for Adult Literacy Scheme Co-ordinators. Underlying the funding by Cheshire County Council for the project is the assumption that the results will be available for all practitioners and that the tools of measurement may be used by other Adult Literacy Co-ordinators in the County. It is intended, therefore, that this research should result in practical outcomes in which methods of assessment will involve active participation by students as well as by tutors, becoming part of the learning process. It is hypothesised that this kind of co-operation could lead ultimately to self-directed learning and student-independence. For the purposes of this research, a balance is attempted in the use of assessment tools, between standardised tests and informal methods. The study provides facts about students! reading habits; as well as their reading levels, their spelling levels, their handwriting, their writing skills and their writing habits. The study seeks to show the students' feelings towards education, their educational attainments and the type of school which they attended. The study also attempts to come to some measurement of those aspects of student personality which relate to confidence, by means of tests and questionnaires. The study concludes with an examination of the link between cognitive and affective progress.