Globally optimal parameters for on-line learning in multilayer neural networks

We present a framework for calculating globally optimal parameters, within a given time frame, for on-line learning in multilayer neural networks. We demonstrate the capability of this method by computing optimal learning rates in typical learning scenarios. A similar treatment allows one to determine the relevance of related training algorithms based on modifications to the basic gradient descent rule as well as to compare different training methods.

Globally optimal learning rates in multilayer neural networks

A method for calculating the globally optimal learning rate in on-line gradient-descent training of multilayer neural networks is presented. The method is based on a variational approach which maximizes the decrease in generalization error over a given time frame. We demonstrate the method by computing optimal learning rates in typical learning scenarios. The method can also be employed when different learning rates are allowed for different parameter vectors as well as to determine the relevance of related training algorithms based on modifications to the basic gradient descent rule.

The role of stochasticity in an information-optimal neural population code

In this paper we consider the optimisation of Shannon mutual information (MI) in the context of two model neural systems The first is a stochastic pooling network (population) of McCulloch-Pitts (MP) type neurons (logical threshold units) subject to stochastic forcing; the second is (in a rate coding paradigm) a population of neurons that each displays Poisson statistics (the so called 'Poisson neuron'). The mutual information is optimised as a function of a parameter that characterises the 'noise level'-in the MP array this parameter is the standard deviation of the noise, in the population of Poisson neurons it is the window length used to determine the spike count. In both systems we find that the emergent neural architecture and; hence, code that maximises the MI is strongly influenced by the noise level. Low noise levels leads to a heterogeneous distribution of neural parameters (diversity), whereas, medium to high noise levels result in the clustering of neural parameters into distinct groups that can be interpreted as subpopulations In both cases the number of subpopulations increases with a decrease in noise level. Our results suggest that subpopulations are a generic feature of an information optimal neural population.

Financial liberalization and dynamics of firm-level financing and investment decisions in the Southeast Asian countries

This thesis examines the dynamics of firm-level financing and investment decisions for six Southeast Asian countries. The study provides empirical evidence on the impacts of changes in the firm-level financing decisions during the period of financial liberalization by considering the debt and equity financing decisions of a set of non-financial firms. The empirical results show that firms in Indonesia, Pakistan, and South Korea have relatively faster speed of adjustment than other Southeast Asian countries to attain optimal debt and equity ratios in response to banking sector and stock market liberalization. In addition, contrary to widely held belief that firms adjust their financial ratios to industry levels, the results indicate that industry factors do not significantly impact on the speed of capital structure adjustments. This study also shows that non-linear estimation methods are more appropriate than linear estimation methods for capturing changes in capital structure. The empirical results also show that international stock market integration of these countries has significantly reduced the equity risk premium as well as the firm-level cost of equity capital. Thus stock market liberalization is associated with a decrease in the cost of equity capital of the firms. Developments in the securities markets infrastructure have also reduced the cost of equity capital. However, with increased integration there is the possibility of capital outflows from the emerging markets, which might reverse the pattern of decrease in cost of capital in these markets.

Multi-level optimization of a fiber transmission system via nonlinearity management

linearity management is explored as a complete tool to obtain maximum transmission reach in a WDM fiber transmission system, making it possible to optimize multiple system parameters, including optimal dispersion pre-compensation, with fast simulations based on the continuous-wave approximation.

When does leverage hurt productivity growth? A firm-level analysis:a firm-level analysis

In the wake of the global financial crisis, several macroeconomic contributions have highlighted the risks of excessive credit expansion. In particular, too much finance can have a negative impact on growth. We examine the microeconomic foundations of this argument, positing a non-monotonic relationship between leverage and firm-level productivity growth in the spirit of the trade-off theory of capital structure. A threshold regression model estimated on a sample of Central and Eastern European countries confirms that TFP growth increases with leverage until the latter reaches a critical threshold beyond which leverage lowers TFP growth. This estimate can provide guidance to firms and policy makers on identifying "excessive" leverage. We find similar non-monotonic relationships between leverage and proxies for firm value. Our results are a first step in bridging the gap between the literature on optimal capital structure and the wider macro literature on the finance-growth nexus. © 2012 Elsevier Ltd.

Reflecting on time, timing and timeliness in public sector supply networks

Despite recent research on time (e.g. Hedaa & Törnroos, 2001), consideration of the time dimension in data collection, analysis and interpretation in research in supply networks is, to date, still limited. Drawing on a body of literature from organization studies, and empirical findings from a six-year action research programme and a related study of network learning, we reflect on time, timing and timeliness in interorganizational networks. The empirical setting is supply networks in the English health sector wherein we identify and elaborate various issues of time, within the case and in terms of research process. Our analysis is wide-ranging and multi-level, from the global (e.g. identifying the notion of life cycles) to the particular (e.g. different cycle times in supply, such as daily for deliveries and yearly for contracts). We discuss the ‘speeding up’ of inter-organizational ‘e’ time and tensions with other time demands. In closing the paper, we relate our conclusions to the future conduct of the research programme and supply research more generally, and to the practice of managing supply (in) networks.

Development of a passive MEG stimulus for measurement of the binaural masking level difference

The ability to hear a target signal over background noise is an important aspect of efficient hearing in everyday situations. This mechanism depends on binaural hearing whenever there are differences in the inter-aural timing of inputs from the noise and the signal. Impairments in binaural hearing may underlie some auditory processing disorders, for example temporal-lobe epilepsies. The binaural masking level difference (BMLD) measures the advantage in detecting a tone whose inter-aural phase differs from that of the masking noise. BMLD’s are typically estimated psychophysically, but this is challenging in children or those with cognitive impairments. The aim of this doctorate is to design a passive measure of BMLD using magnetoencephalography (MEG) and test this in adults, children and patients with different types of epilepsy. The stimulus consists of Gaussian background noise with 500-Hz tones presented binaurally either in-phase or 180° out-of-phase between the ears. Source modelling provides the N1m amplitude for the in-phase and out-of-phase tones, representing the extent of signal perception over background noise. The passive BMLD stimulus is successfully used as a measure of binaural hearing capabilities in participants who would otherwise be unable to undertake a psychophysical task.

Multi-level genetic algorithm for the resource-constrained re-entrant scheduling problem in the flow shop

The re-entrant flow shop scheduling problem (RFSP) is regarded as a NP-hard problem and attracted the attention of both researchers and industry. Current approach attempts to minimize the makespan of RFSP without considering the interdependency between the resource constraints and the re-entrant probability. This paper proposed Multi-level genetic algorithm (GA) by including the co-related re-entrant possibility and production mode in multi-level chromosome encoding. Repair operator is incorporated in the Multi-level genetic algorithm so as to revise the infeasible solution by resolving the resource conflict. With the objective of minimizing the makespan, Multi-level genetic algorithm (GA) is proposed and ANOVA is used to fine tune the parameter setting of GA. The experiment shows that the proposed approach is more effective to find the near-optimal schedule than the simulated annealing algorithm for both small-size problem and large-size problem. © 2013 Published by Elsevier Ltd.

Multi-level optimization of a fiber transmission system via nonlinearity management

Nonlinearity management is explored as a complete tool to obtain maximum transmission reach in a WDM fiber transmission system, making it possible to optimize multiple system parameters, including optimal dispersion pre-compensation, with fast simulations based on the continuous-wave approximation. © 2006 Optical Society of America.

Optimal Control of Heterogeneous Systems

Цветомир Цачев - В настоящия доклад се прави преглед на някои резултати от областта на оптималното управление на непрекъснатите хетерогенни системи, публикувани в периодичната научна литература в последните години. Една динамична система се нарича хетерогенна, ако всеки от нейните елементи има собствена динамиката. Тук разглеждаме оптимално управление на системи, чиято хетерогенност се описва с едномерен или двумерен параметър – на всяка стойност на параметъра отговаря съответен елемент на системата. Хетерогенните динамични системи се използват за моделиране на процеси в икономиката, епидемиологията, биологията, опазване на обществената сигурност (ограничаване на използването на наркотици) и др. Тук разглеждаме модел на оптимално инвестиране в образование на макроикономическо ниво [11], на ограничаване на последствията от разпространението на СПИН [9], на пазар на права за въглеродни емисии [3, 4] и на оптимален макроикономически растеж при повишаване на нивото на върховите технологии [1]. Ключови думи: оптимално управление, непрекъснати хетерогенни динамични системи, приложения в икономиката и епидемиолегията

The Long-Term impact of Business Support? - Exploring the Role of Evaluation Timing using Micro Data

The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.

The long-term impact of business support? - Exploring the role of evaluation timing using micro data

The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.

Közjavak optimális előállítása (Optimal production of public goods)

A közjavak közgazdaságilag optimális szintjének előállítása piaci körülmények között általában nehézségekbe ütközik. Napjainkban számos országban többféle közjószág áll rendelkezésre, a szakirodalomban pedig például a nyugdíjrendszer egyes elemeinek közjószágjellegével kapcsolatos felvetések is megjelentek már. Ezzel összefüggésben is érdekes a kérdés, milyen körülmények között fordulhat elő, hogy racionális egyéni döntéshozók egyénileg optimális döntéseikkel valamely közjószág optimális szintjét hozzák létre. Jelen tanulmány ezzel a kérdéssel foglalkozik. / === / It is difficult to produce the economically optimal level of public goods in a market environment. There are many different types of public goods, and today even some aspects of the pension system are considered as such. Still, it is an interesting question if individually optimal decisions made by rational individuals could lead to an optimal level of public goods. The paper attempts to analyze this question.

A nemzetgazdasági versenyképesség sportszakmai és gazdasági aspektusai = Sport and economic aspects of competitiveness on national level

Tanulmányunk a gazdasági versenyképességgel, kiemelten annak nemzetgazdasági szintű vetületével és a sport esetében történő értelmezésével foglakozik. A gazdasági versenyképesség esetén kiemelten kezeljük az IMD és a WEF versenyképességi rangsorait, a sport esetén pedig szétválasztjuk a hivatásos és a szabadidősportot. A hivatásos sport esetén bemutatjuk a sportszakmai versenyképességet indikáló és a sportszakmai versenyképességre hatással lévő gazdasági és társadalmi mutatókat egyaránt. Összehasonlítási csoportot képeztünk, amelyben Magyarország és a környező országok szerepelnek és a komparatív elemzés kiterjed a gazdasági és a sportszakmai versenyképességre, valamint a sportszakmai versenyképességre ható gazdasági és társadalmi tényezőkre egyaránt. A sportszakmai versenyképességet az olimpiai érmek számával és azok pontértékével mérjük, amit az olimpiák teljes történelmére és az elmúlt 20 év különböző szakaszaira egyaránt vizsgálunk, míg a gazdasági és társadalmi tényezőket csak a mondanivalónk szempontjából legrelevánsabb évekre, az új évezredre vizsgálunk. A hivatásos sporttal kapcsolatos versenyképességi kérdésekből azt a következtetést vontuk le, hogy Magyarország történelmi sportszakmai eredményességének fenntartását a jelen gazdasági és társadalmi tényezők nem igazolják, sőt az elmúlt időszak visszaesését támasztják alá és a Londoni olimpián való szereplésünkkel kapcsolatban inkább az összehasonlítási csoporton belüli további visszacsúszást, mintsem az eredmény javulását támogatják. A tanulmányban azt állítjuk, hogy egyéni, vállalati és makrogazdasági versenyképességet is javíthat a szabadidősport. Mikro szinten, majd makrogazdasági szinten elemeztük a szabadidősport hatásait, valamint próbáltunk választ keresni arra a kérdésre, hogy hogyan válhat az egyén, a vállalat és végső célként a gazdaság versenyképesebbé a fizikai aktivitás által. A kevesebb betegség és egészségügyi kiadás, vagy éppen a kedvezőbb várható élettartami mutatók mellett termelékenység-növekedés, a versenyképességi rangsorokban pedig előkelőbb helyezések érhetők el. ______ Our paper tackles the concept of competitiveness in the national level and interprets it also in the field of sport as well. In the economics field we focus on the competitiveness rankings of IMD and WEF and in the sport field we differentiate between professional and leisure sport. In the case of professional sport we introduce the measures of sport competitiveness and its influencing economic and social factors as well. We have made a peer group which contains Hungary and its neighboring countries and the comparative study tackles the sport competitiveness and the influencing economic and social factors as well. We measure sport competitiveness with the Olympic medal count and the medals point value, which is counted in the whole Olympic history, and different phases of the last 20 years. The economic and social factors are compared only in the new millennia as this is the most relevant time frame of this study. From the competitiveness analysis of professional sport we concluded that the maintenance of Hungary’s historical sport successes is not proved by nowadays economic and social factors, however they support the past years decline. These factors also indicate that in London (2012)we would rather slip one more position back in the peer group, than rise again from our ashes. In our opinion leisure sport could enhance the competitiveness of individuals, companies, and economy also. We analysed the effects of leisure sport on the microeconomic and macroeconomic level, and tried to find answer to that question how could be individuals, companies, and economy more competitive through leisure sport. Besides less illness and health care expenditures, longer life expectancy, productivity growth, countries could be well placed in competitiveness’ rankings.