Globally optimal on-line learning rules for multi-layer neural networks

We present a method for determining the globally optimal on-line learning rule for a soft committee machine under a statistical mechanics framework. This rule maximizes the total reduction in generalization error over the whole learning process. A simple example demonstrates that the locally optimal rule, which maximizes the rate of decrease in generalization error, may perform poorly in comparison.

The influence of face and group orientation on the perception of luxury goods:a four market study of East Asian consumers

Purpose: The paper aims to further extend our understanding by assessing the extent to which two prominent cultural values in East Asia i.e. face saving and group orientation drive consumers' perceptions of luxury goods across four East Asian markets. Design/methodology/approach: A multi-methods research approach was adopted consisting of: an expert panel of close to 70 participants, group discussions with five extended East Asian families, personal interviews with eight East Asian scholars, a pilot test with over 50 East Asian graduate students and a multi-market survey of 443 consumer respondents in Beijing, Tokyo, Singapore and Hanoi. Findings: The authors extend previous conceptual studies by empirically investigating the impact of these two cultural values on the perception of luxury among East Asian societies. Specifically the study reveals that across all four markets face saving has the strongest influence on the conspicuous and hedonistic dimensions of luxury, group orientation meanwhile is the strongest predictor of the quality, extended self and exclusivity dimensions of luxury. Collectively these two cultural values significantly influence East Asian perceptions of luxury. Overall, the findings reiterate the importance of understanding different cultural values and their influence across different East Asian societies. Practical implications: The findings have important implications for managers of western luxury branded goods that are seeking to penetrate East Asian markets or seek to serve East Asian consumers. Specifically, to assist with developing suitable brand positioning, products, services, communications and pricing strategies. Originality/value: This study contributes to our understanding of the subject by exploring the impact of face saving and group orientation on the perception of luxury goods across four East Asian countries. Several directions for future research are suggested. © Emerald Group Publishing Limited.

New product development proficiency and multi-country product rollout timeliness

Purpose: The purpose of this paper is to address a gap in the understanding of the indirect effects of marketing and technical factors on time efficiency in developing a new product and international new product launch. Design/methodology/approach: This paper adopts a contingency perspective in examining the relationships between antecedents and on-time completion (or timeliness) of new product development (NPD) and international new product rollout (INPR). A conceptual framework is tested based on data obtained on 232 NPD projects undertaken by Korean firms. Findings: The results show that NPD proficiencies mediate to a greater or lesser extent the effects of key antecedents (e.g. cross-functional linkages, project fit with available marketing resources, and effective coordination of headquarters-subsidiary/agents' activities) on timeliness in NPD and INPR. Research limitations/implications: Empirical research on the role of marketing and technical proficiencies in improving NPD timeliness and rollout timeliness in the context of international NPD affirms the importance of adopting a contingency perspective in examining the antecedents of NPD and multi-market entry timeliness. Practical implications: This paper lends insight into the role of overseas subsidiaries or agents in helping to build the technical proficiencies of emerging country companies. Originality/value: This is the first review focusing on the mediating influences on time dimensions (e.g. timeliness) in multi-country product launches. © Emerald Group Publishing Limited.

Incorporating curvature information into on-line learning

We analyse the dynamics of a number of second order on-line learning algorithms training multi-layer neural networks, using the methods of statistical mechanics. We first consider on-line Newton's method, which is known to provide optimal asymptotic performance. We determine the asymptotic generalization error decay for a soft committee machine, which is shown to compare favourably with the result for standard gradient descent. Matrix momentum provides a practical approximation to this method by allowing an efficient inversion of the Hessian. We consider an idealized matrix momentum algorithm which requires access to the Hessian and find close correspondence with the dynamics of on-line Newton's method. In practice, the Hessian will not be known on-line and we therefore consider matrix momentum using a single example approximation to the Hessian. In this case good asymptotic performance may still be achieved, but the algorithm is now sensitive to parameter choice because of noise in the Hessian estimate. On-line Newton's method is not appropriate during the transient learning phase, since a suboptimal unstable fixed point of the gradient descent dynamics becomes stable for this algorithm. A principled alternative is to use Amari's natural gradient learning algorithm and we show how this method provides a significant reduction in learning time when compared to gradient descent, while retaining the asymptotic performance of on-line Newton's method.

Goal detection from natural language queries

This paper aims to identify the communication goal(s) of a user's information-seeking query out of a finite set of within-domain goals in natural language queries. It proposes using Tree-Augmented Naive Bayes networks (TANs) for goal detection. The problem is formulated as N binary decisions, and each is performed by a TAN. Comparative study has been carried out to compare the performance with Naive Bayes, fully-connected TANs, and multi-layer neural networks. Experimental results show that TANs consistently give better results when tested on the ATIS and DARPA Communicator corpora.

Where do bright ideas occur in our brain? Meta-analytic evidence from neuroimaging studies of domain-specific creativity

Many studies have assessed the neural underpinnings of creativity, failing to find a clear anatomical localization. We aimed to provide evidence for a multi-componential neural system for creativity. We applied a general activation likelihood estimation (ALE) meta-analysis to 45 fMRI studies. Three individual ALE analyses were performed to assess creativity in different cognitive domains (Musical, Verbal, and Visuo-spatial). The general ALE revealed that creativity relies on clusters of activations in the bilateral occipital, parietal, frontal, and temporal lobes. The individual ALE revealed different maximal activation in different domains. Musical creativity yields activations in the bilateral medial frontal gyrus, in the left cingulate gyrus, middle frontal gyrus, and inferior parietal lobule and in the right postcentral and fusiform gyri. Verbal creativity yields activations mainly located in the left hemisphere, in the prefrontal cortex, middle and superior temporal gyri, inferior parietal lobule, postcentral and supramarginal gyri, middle occipital gyrus, and insula. The right inferior frontal gyrus and the lingual gyrus were also activated. Visuo-spatial creativity activates the right middle and inferior frontal gyri, the bilateral thalamus and the left precentral gyrus. This evidence suggests that creativity relies on multi-componential neural networks and that different creativity domains depend on different brain regions.

The real effects of banking supervision:evidence from enforcement actions

We present a novel way to examine macro-financial linkages by focusing on the real effects of bank supervisors’ enforcement actions. Exploiting plausibly exogenous variation in supervisory monitoring intensity, we show that enforcement actions in single-market banks trigger temporarily large adverse effects for the macroeconomy by reducing personal income growth, the number of establishments, and increasing unemployment. These effects are related to contractions in bank lending and liquidity creation, and are more pronounced when we consider enforcement actions on both single-market and multi-market banks, and in counties with fewer banks and greater external financial dependence.

Marking high-technology market evolution through the foci of market stories:the case of local area networks

Previous research suggests that changing consumer and producer knowledge structures play a role in market evolution and that the sociocognitive processes of product markets are revealed in the sensemaking stories of market actors that are rebroadcasted in commercial publications. In this article, the authors lend further support to the story-based nature of market sensemaking and the use of the sociocognitive approach in explaining the evolution of high-technology markets. They examine the content (i.e., subject matter or topic) and volume (i.e., the number) of market stories and the extent to which content and volume of market stories evolve as a technology emerges. Data were obtained from a content analysis of 10,412 article abstracts, published in key trade journals, pertaining to Local Area Network (LAN) technologies and spanning the period 1981 to 2000. Hypotheses concerning the evolving nature (content and volume) of market stories in technology evolution are tested. The analysis identified four categories of market stories - technical, product availability, product adoption, and product discontinuation. The findings show that the emerging technology passes initially through a 'technical-intensive' phase whereby technology related stories dominate, through a 'supply-push' phase, in which stories presenting products embracing the technology tend to exceed technical stories while there is a rise in the number of product adoption reference stories, to a 'product-focus' phase, with stories predominantly focusing on product availability. Overall story volume declines when a technology matures as the need for sensemaking reduces. When stories about product discontinuation surface, these signal the decline of current technology. New technologies that fail to maintain the 'product-focus' stage also reflect limited market acceptance. The article also discusses the theoretical and managerial implications of the study's findings. © 2002 Elsevier Science Inc. All rights reserved.

Market orientation of service networks:direct and indirect effects on sustained competitive advantage

Market orientation is an organization-wide concept that helps explain sustained competitive advantage (SCA). Since networks become ever more important, especially in the service sector, there is need to expand the concept of MO to a network setting. In line with Narver and Slater (1990), the concept of Market Orientation of Networks (MONW) is developed. This study indicates how MONW relates to the resource-based view (RBV) of the firm and the industrial organization (IO) view in explaining SCA. It is argued that MONW has direct and indirect effects on SCA. More precisely, the antecedent effect of MONW to resources and industry structure is considered.

A socio-economic approach to online vision graph generation and handover in distributed smart camera networks

In this paper we propose an approach based on self-interested autonomous cameras, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to grow the vision graph during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online which permits the addition and removal cameras to the network during runtime and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multi-camera calibration can be avoided. © 2011 IEEE.

Gain switched multi-carrier transmitter and pilot tone based receiver for long reach access networks

A novel and cost effective long reach PON downlink scenario is proposed employing a multi-carrier transmitter and pilot tone aided direct detection at the receiver. Error free performance with QPSK and 50km transmission is presented. © 2012 OSA.

Dual-polarization multi-band OFDM signals for next generation core networks

Dual-polarization multi-band orthogonal frequency-division multiplexing (DP-MB-OFDM) signals are optimized at data rates up to 500 Gb/s in dispersion compensation fiber (DCF)-free long-haul links. We compare different polarization crosstalk compensation techniques and explore the DP-MB-OFDM transmission distance limitations. In addition, the impact of the OFDM subcarrier number and high-level modulation format on the transmission performance are also investigated. Finally, a comparison is made between DP-MB-OFDM and the industrial solution of single-carrier DP quaternary phase-shift keying (DP-QPSK) at 1000 km.

Exposing market mechanism design trade-offs via multi-objective evolutionary search

Market mechanisms are a means by which resources in contention can be allocated between contending parties, both in human economies and those populated by software agents. Designing such mechanisms has traditionally been carried out by hand, and more recently by automation. Assessing these mechanisms typically involves them being evaluated with respect to multiple conflicting objectives, which can often be nonlinear, noisy, and expensive to compute. For typical performance objectives, it is known that designed mechanisms often fall short on being optimal across all objectives simultaneously. However, in all previous automated approaches, either only a single objective is considered, or else the multiple performance objectives are combined into a single objective. In this paper we do not aggregate objectives, instead considering a direct, novel application of multi-objective evolutionary algorithms (MOEAs) to the problem of automated mechanism design. This allows the automatic discovery of trade-offs that such objectives impose on mechanisms. We pose the problem of mechanism design, specifically for the class of linear redistribution mechanisms, as a naturally existing multi-objective optimisation problem. We apply a modified version of NSGA-II in order to design mechanisms within this class, given economically relevant objectives such as welfare and fairness. This application of NSGA-II exposes tradeoffs between objectives, revealing relationships between them that were otherwise unknown for this mechanism class. The understanding of the trade-off gained from the application of MOEAs can thus help practitioners with an insightful application of discovered mechanisms in their respective real/artificial markets.

Improved adaptivity and robustness in decentralised multi-camera networks

In this paper we present increased adaptivity and robustness in distributed object tracking by multi-camera networks using a socio-economic mechanism for learning the vision graph. To build-up the vision graph autonomously within a distributed smart-camera network, we use an ant-colony inspired mechanism, which exchanges responsibility for tracking objects using Vickrey auctions. Employing the learnt vision graph allows the system to optimise its communication continuously. Since distributed smart camera networks are prone to uncertainties in individual cameras, such as failures or changes in extrinsic parameters, the vision graph should be sufficiently robust and adaptable during runtime to enable seamless tracking and optimised communication. To better reflect real smart-camera platforms and networks, we consider that communication and handover are not instantaneous, and that cameras may be added, removed or their properties changed during runtime. Using our dynamic socio-economic approach, the network is able to continue tracking objects well, despite all these uncertainties, and in some cases even with improved performance. This demonstrates the adaptivity and robustness of our approach.