24 resultados para LEARNING-PROBLEMS
em Aston University Research Archive
Resumo:
The Vapnik-Chervonenkis (VC) dimension is a combinatorial measure of a certain class of machine learning problems, which may be used to obtain upper and lower bounds on the number of training examples needed to learn to prescribed levels of accuracy. Most of the known bounds apply to the Probably Approximately Correct (PAC) framework, which is the framework within which we work in this paper. For a learning problem with some known VC dimension, much is known about the order of growth of the sample-size requirement of the problem, as a function of the PAC parameters. The exact value of sample-size requirement is however less well-known, and depends heavily on the particular learning algorithm being used. This is a major obstacle to the practical application of the VC dimension. Hence it is important to know exactly how the sample-size requirement depends on VC dimension, and with that in mind, we describe a general algorithm for learning problems having VC dimension 1. Its sample-size requirement is minimal (as a function of the PAC parameters), and turns out to be the same for all non-trivial learning problems having VC dimension 1. While the method used cannot be naively generalised to higher VC dimension, it suggests that optimal algorithm-dependent bounds may improve substantially on current upper bounds.
Resumo:
The aim of this thesis is to explore key aspects and problems of the institutionalised teaching and learning of German language and culture in the context of German Studies in British Higher Education (HE). This investigation focuses on teaching and learning experiences in one department of German Studies in the UK, which is the micro-context of the present study, in order to provide an in-depth insight into real-life problems, strengths and weaknesses as they occur in the practice of teaching and learning German. Following Lamb (2004) and Holliday (1994), the present study acts on the assumption that each micro-context does not exist in vacuo but is always embedded in a wider socio-political and education environment, namely the macro-context, which largely determines how and what is taught. The macro-analysis of the present study surveys the socio-political developments that have recently affected the sector of modern languages and specifically the discipline of German Studies in the UK. It demonstrates the impact they have had on teaching and learning German at the undergraduate level in Britain. This context is interesting inasmuch as the situation in Britain is to a large extent a paradigmatic example of the developments in German Studies in English-speaking countries. Subsequently, the present study explores learning experiences of a group of thirty-five first year students. It focuses on their previous experiences in learning German, exposure to the target language, motivation, learning strategies and difficulties encountered, when learning German at the tertiary level. Then, on the basis of interviews with five lecturers of German, teaching experience in the context under study is explored, problems and successful teaching strategies discussed.
Resumo:
The performance of feed-forward neural networks in real applications can be often be improved significantly if use is made of a-priori information. For interpolation problems this prior knowledge frequently includes smoothness requirements on the network mapping, and can be imposed by the addition to the error function of suitable regularization terms. The new error function, however, now depends on the derivatives of the network mapping, and so the standard back-propagation algorithm cannot be applied. In this paper, we derive a computationally efficient learning algorithm, for a feed-forward network of arbitrary topology, which can be used to minimize the new error function. Networks having a single hidden layer, for which the learning algorithm simplifies, are treated as a special case.
Resumo:
The performance of seven minimization algorithms are compared on five neural network problems. These include a variable-step-size algorithm, conjugate gradient, and several methods with explicit analytic or numerical approximations to the Hessian.
Resumo:
Neural networks are usually curved statistical models. They do not have finite dimensional sufficient statistics, so on-line learning on the model itself inevitably loses information. In this paper we propose a new scheme for training curved models, inspired by the ideas of ancillary statistics and adaptive critics. At each point estimate an auxiliary flat model (exponential family) is built to locally accommodate both the usual statistic (tangent to the model) and an ancillary statistic (normal to the model). The auxiliary model plays a role in determining credit assignment analogous to that played by an adaptive critic in solving temporal problems. The method is illustrated with the Cauchy model and the algorithm is proved to be asymptotically efficient.
Resumo:
A theoretical model is presented which describes selection in a genetic algorithm (GA) under a stochastic fitness measure and correctly accounts for finite population effects. Although this model describes a number of selection schemes, we only consider Boltzmann selection in detail here as results for this form of selection are particularly transparent when fitness is corrupted by additive Gaussian noise. Finite population effects are shown to be of fundamental importance in this case, as the noise has no effect in the infinite population limit. In the limit of weak selection we show how the effects of any Gaussian noise can be removed by increasing the population size appropriately. The theory is tested on two closely related problems: the one-max problem corrupted by Gaussian noise and generalization in a perceptron with binary weights. The averaged dynamics can be accurately modelled for both problems using a formalism which describes the dynamics of the GA using methods from statistical mechanics. The second problem is a simple example of a learning problem and by considering this problem we show how the accurate characterization of noise in the fitness evaluation may be relevant in machine learning. The training error (negative fitness) is the number of misclassified training examples in a batch and can be considered as a noisy version of the generalization error if an independent batch is used for each evaluation. The noise is due to the finite batch size and in the limit of large problem size and weak selection we show how the effect of this noise can be removed by increasing the population size. This allows the optimal batch size to be determined, which minimizes computation time as well as the total number of training examples required.
Resumo:
Public policy becomes managerial practice through a process of implementation. There is an established literature within Implementation Studies which explains the variables and some of the processes involved in implementation, but less attention has been focused upon how public service managers convert new policy initiatives into practice. The research proposes that managers and their organisations have to go through a process of learning in order to achieve the implementation of public policy. Data was collected over a five year period from four case studies of capital investment appraisal in the British National Health Service. Further data was collected from taped interviews by key actors within the case studies. The findings suggest that managers do learn to implement policy and four factors are important in this learning process. These are; (i) the nature of bureaucratic responsibility; (ii) the motivation of actors towards learning; (iii) the passage of time which allows for the development of competence and (iv) the use of project team structures. The research has demonstrated that the conversion of policy into practice occurs through the operationalisation of solutions to policy problems via job tasks. As such it suggests that in understanding how policy is implemented, technical learning is more important than cultural learning, in this context. In conclusion, a "Model of Learned Implementation" is presented, together with a discussion of some of the implications of the research. These are the possible use of more pilot projects for new policy initiatives and the more systematic diffusion of knowledge about implementation solutions.
Resumo:
We investigated the ability to learn new words in a group of 22 adults with developmental dyslexia/dysgraphia and the relationship between their learning and spelling problems. We identified a deficit that affected the ability to learn both spoken and written new words (lexical learning deficit). There were no comparable problems in learning other kinds of representations (lexical/semantic and visual) and the deficit could not be explained in terms of more traditional phonological deficits associated with dyslexia (phonological awareness, phonological STM). Written new word learning accounted for further variance in the severity of the dysgraphia after phonological abilities had been partialled out. We suggest that lexical learning may be an independent ability needed to create lexical/formal representations from a series of independent units. Theoretical and clinical implications are discussed. © 2005 Psychology Press Ltd.
Resumo:
This paper reviews the approach to multidisciplinary and placement education in UK schools of pharmacy. The methodology involved triangulation of course documentation, staff interviews and a final year student survey. Staff members were supportive of multidisciplinary learning. The advantages were development of a wider appreciation of the students? future professional role and better understanding of the roles of other professional groups. The barriers were logistics (student numbers; multiple sites; different timetables), the achievement of balanced numbers between disciplines and engagement of students from all participating disciplines. Placement education was offered by all schools, predominantly in hospital settings. Key problems were funding and the lack of staff resources. Currently, multidisciplinary learning within the UK for pharmacy students is inadequate and is coupled with relatively low levels of placement education. In order for things to change, there should be a review of funding and support from government and the private sector employers.
Resumo:
There are been a resurgence of interest in the neural networks field in recent years, provoked in part by the discovery of the properties of multi-layer networks. This interest has in turn raised questions about the possibility of making neural network behaviour more adaptive by automating some of the processes involved. Prior to these particular questions, the process of determining the parameters and network architecture required to solve a given problem had been a time consuming activity. A number of researchers have attempted to address these issues by automating these processes, concentrating in particular on the dynamic selection of an appropriate network architecture.The work presented here specifically explores the area of automatic architecture selection; it focuses upon the design and implementation of a dynamic algorithm based on the Back-Propagation learning algorithm. The algorithm constructs a single hidden layer as the learning process proceeds using individual pattern error as the basis of unit insertion. This algorithm is applied to several problems of differing type and complexity and is found to produce near minimal architectures that are shown to have a high level of generalisation ability.
Resumo:
There has been substantial research into the role of distance learning in education. Despite the rise in the popularity and practice of this form of learning in business, there has not been a parallel increase in the amount of research carried out in this field. An extensive investigation was conducted into the entire distance learning system of a multi-national company with particular emphasis on the design, implementation and evaluation of the materials. In addition, the performance and attitudes of trainees were examined. The results of a comparative study indicated that trainees using distance learning had significantly higher test scores than trainees using conventional face-to-face training. The influence of the previous distance learning experience, educational background and selected study environment of trainees was investigated. Trainees with previous experience of distance learning were more likely to complete the course and with significantly higher test scores than trainees with no previous experience. The more advanced the educational background of trainees, the greater the likelihood of their completing the course, although there was no significant difference in the test scores achieved. Trainees preferred to use the materials at home and those opting to study in this environment scored significantly higher than those studying in the office, the study room at work or in a combination of environments. The influence of learning styles (Kolb, 1976) was tested. The results indicated that the convergers had the greatest completion rates and scored significantly higher than trainees with the assimilator, accommodator and diverger learning styles. The attitudes of the trainees, supervisors and trainers were examined using questionnaire, interview and discussion techniques. The findings highlighted the potential problems of lack of awareness and low motivation which could prove to be major obstacles to the success of distance learning in business.
Resumo:
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.
Resumo:
This article examines the current risk regulation regime, within the English National Health Service (NHS), by investigating the two, sometimes conflicting, approaches to risk embodied within the field of policies towards patient safety. The first approach focuses on promoting accountability and is built on legal principles surrounding negligence and competence. The second approach focuses on promoting learning from previous mistakes and near-misses, and is built on the development of a ‘safety culture’. Previous work has drawn attention to problems associated with risk-based regulation when faced with the dual imperatives of accountability and organisational learning. The article develops this by considering whether the NHS patient safety regime demonstrates the coexistence of two different risk regulation regimes, or merely one regime with contradictory elements. It uses the heuristic device of ‘institutional logics’ to examine the coexistence of and interrelationship between ‘organisational learning’ and ‘accountability’ logics driving risk regulation in health care.
Resumo:
As a global profession, engineering is integral to the maintenance and further development of society. Indeed, contemporary social problems requiring engineering solutions are not only a consequence of natural and ‘manmade’ disasters (such as the Japanese earthquake or the oil leakage in the Gulf of Mexico) but also encapsulate 21st Century dilemmas around sustainability, poverty and pollution [2,6,7]. Given the complexity of such problems and the constant need for innovation, the demand for engineering education to provide a ready supply of suitably qualified engineering graduates, able to make innovative decisions has never been higher [3,5]. Bearing this in mind, and taking account problems of attrition in engineering education [1,6,4] innovation in the way in which the curriculum is developed and delivered is crucial. CDIO [Conceive, Design, Implement, Operate] provides a potentially ground-breaking solution to such dilemmas. Aimed at equipping students with practical engineering skills supported by the necessary theoretical background, CDIO could potentially change the way engineering is perceived and experienced within higher education. Aston University introduced CDIO into its Mechanical Engineering and Design programmes in October 2011. From its induction, engineering education researchers have ‘shadowed’ the staff responsible for developing and teaching the programme. Utilising an Action Research Design, and adopting a mixed methodological research design, the researchers have worked closely with the teaching team to critically reflect on the processes involved in introducing CDIO into the curriculum. Concurrently, research has been conducted to capture students’ perspectives of CDIO. In evaluating the introduction of CDIO at Aston, the researchers have developed a distinctive research strategy with which to evaluate CDIO. It is the emergent findings from this research that form the basis of this paper. Although early-on in its development CDIO is making a significant difference to engineering education at the University. The paper draws attention to pedagogical, practical and professional issues – discussing each one in turn and in doing so critically analysing the value of CDIO from academic, student and industrial perspectives. The paper concludes by noting that whilst CDIO represents a forwardthinking approach to engineering education, the need for constant innovation in learning and teaching should not be forgotten. Indeed, engineering education needs to put itself at the forefront of pedagogic practice. Providing all-rounded engineers, ready to take on the challenges of the 21st Century!
Resumo:
The paper proffers a tentative conceptualisation of the “small business strategic learning process”, demonstrating the complexity of the small firm learning and management task. The framework, built upon personal construct theory and learning theories, is elaborated through the grounding of relevant areas of the strategic management literature in an understanding of the distinctive managerial and behavioural features of the small business. The framework is then utilised to underpin consideration of the concepts of “organisational learning” and the “learning organisation” within a small firm developmental context. It is suggested that whilst organisational learning may be a key and effective small business management approach to underpin sustainable development, the learning organisation, as currently conceived in the mainstream literature, fails to recognise and address the idiosyncrasies, problems and constraints relating to sustainable small business development. There does appear, however, to be great potential for extending understanding of the learning organisation concept into the small business context. An indicative research agenda is suggested.