The role of biases in on-line learning of two-layer networks

The influence of biases on the learning dynamics of a two-layer neural network, a normalized soft-committee machine, is studied for on-line gradient descent learning. Within a statistical mechanics framework, numerical studies show that the inclusion of adjustable biases dramatically alters the learning dynamics found previously. The symmetric phase which has often been predominant in the original model all but disappears for a non-degenerate bias task. The extended model furthermore exhibits a much richer dynamical behavior, e.g. attractive suboptimal symmetric phases even for realizable cases and noiseless data.

Biases in approximating log production

Most empirical work in economic growth assumes either a Cobb–Douglas production function expressed in logs or a log-approximated constant elasticity of substitution specification. Estimates from each are likely biased due to logging the model and the latter can also suffer from approximation bias. We illustrate this with a successful replication of Masanjala and Papagerogiou (The Solow model with CES technology: nonlinearities and parameter heterogeneity, Journal of Applied Econometrics 2004; 19: 171–201) and then estimate both models in levels to avoid these biases. Our estimation in levels gives results in line with conventional wisdom.

The learning dynamics of a universal approximator

The learning properties of a universal approximator, a normalized committee machine with adjustable biases, are studied for on-line back-propagation learning. Within a statistical mechanics framework, numerical studies show that this model has features which do not exist in previously studied two-layer network models without adjustable biases, e.g., attractive suboptimal symmetric phases even for realizable cases and noiseless data.

Natural images dominate in binocular rivalry

Ecological approaches to perception have demonstrated that information encoding by the visual system is informed by the natural environment, both in terms of simple image attributes like luminance and contrast, and more complex relationships corresponding to Gestalt principles of perceptual organization. Here, we ask if this optimization biases perception of visual inputs that are perceptually bistable. Using the binocular rivalry paradigm, we designed stimuli that varied in either their spatiotemporal amplitude spectra or their phase spectra. We found that noise stimuli with “natural” amplitude spectra (i.e., amplitude content proportional to 1/f, where f is spatial or temporal frequency) dominate over those with any other systematic spectral slope, along both spatial and temporal dimensions. This could not be explained by perceived contrast measurements, and occurred even though all stimuli had equal energy. Calculating the effective contrast following attenuation by a model contrast sensitivity function suggested that the strong contrast dependency of rivalry provides the mechanism by which binocular vision is optimized for viewing natural images. We also compared rivalry between natural and phase-scrambled images and found a strong preference for natural phase spectra that could not be accounted for by observer biases in a control task. We propose that this phase specificity relates to contour information, and arises either from the activity of V1 complex cells, or from later visual areas, consistent with recent neuroimaging and single-cell work. Our findings demonstrate that human vision integrates information across space, time, and phase to select the input most likely to hold behavioral relevance.

Memory for emotional faces in major depression following judgement of physical facial characteristics at encoding

The aim of the present study was to establish if patients with major depression (MD) exhibit a memory bias for sad faces, relative to happy and neutral, when the affective element of the faces is not explicitly processed at encoding. To this end, 16 psychiatric out-patients with MD and 18 healthy, never-depressed controls (HC) were presented with a series of emotional faces and were required to identify the gender of the individuals featured in the photographs. Participants were subsequently given a recognition memory test for these faces. At encoding, patients with MD exhibited a non-significant tendency towards slower gender identification (GI) times, relative to HC, for happy faces. However, the GI times of the two groups did not differ for sad or neutral faces. At memory testing, patients with MD did not exhibit the expected memory bias for sad faces. Similarly, HC did not demonstrate enhanced memory for happy faces. Overall, patients with MD were impaired in their memory for the faces relative to the HC. The current findings are consistent with the proposal that mood-congruent memory biases are contingent upon explicit processing of the emotional element of the to-be-remembered material at encoding.

CEO compensation, option incentives and information disclosure

This paper examines the impact of information disclosure on the valuation of CEO options and the incentives created by those options. Prior executive compensation research in the US has made assumptions about key input variables that can affect the calculation of option values and financial incentives. Accordingly, biases may have ensued due to incomplete information disclosure about noncurrent option grants. Using new data on a sample of UK CEOs, we value executive option holdings and incentives for the first time and estimate the levels of distortion created by the less than complete US-style disclosure requirements. We also investigate the levels of distortion in the UK for the minority of companies that choose to reveal only partial information. Our results suggest that there have to date been few economic biases arising from less than complete information disclosure. Furthermore, we demonstrate that researchers using US data, who made reasonable assumptions about the inputs of noncurrent option grants, are unlikely to have made significant errors when calculating CEO financial incentives or option wealth. However, the recent downturn in the US stock market could result in the same assumptions, producing exaggerated incentive estimates in the future.

The discourse of climate change: a corpus-based approach

Based on Goffman’s definition that frames are general ‘schemata of interpretation’ that people use to ‘locate, perceive, identify, and label’, other scholars have used the concept in a more specific way to analyze media coverage. Frames are used in the sense of organizing devices that allow journalists to select and emphasise topics, to decide ‘what matters’ (Gitlin 1980). Gamson and Modigliani (1989) consider frames as being embedded within ‘media packages’ that can be seen as ‘giving meaning’ to an issue. According to Entman (1993), framing comprises a combination of different activities such as: problem definition, causal interpretation, moral evaluation, and/or treatment recommendation for the item described. Previous research has analysed climate change with the purpose of testing Downs’s model of the issue attention cycle (Trumbo 1996), to uncover media biases in the US press (Boykoff and Boykoff 2004), to highlight differences between nations (Brossard et al. 2004; Grundmann 2007) or to analyze cultural reconstructions of scientific knowledge (Carvalho and Burgess 2005). In this paper we shall present data from a corpus linguistics-based approach. We will be drawing on results of a pilot study conducted in Spring 2008 based on the Nexis news media archive. Based on comparative data from the US, the UK, France and Germany, we aim to show how the climate change issue has been framed differently in these countries and how this framing indicates differences in national climate change policies.

Cascaded Bayesian processes: an account of bias in orientation perception

Following adaptation to an oriented (1-d) signal in central vision, the orientation of subsequently viewed test signals may appear repelled away from or attracted towards the adapting orientation. Small angular differences between the adaptor and test yield 'repulsive' shifts, while large angular differences yield 'attractive' shifts. In peripheral vision, however, both small and large angular differences yield repulsive shifts. To account for these tilt after-effects (TAEs), a cascaded model of orientation estimation that is optimized using hierarchical Bayesian methods is proposed. The model accounts for orientation bias through adaptation-induced losses in information that arise because of signal uncertainties and neural constraints placed upon the propagation of visual information. Repulsive (direct) TAEs arise at early stages of visual processing from adaptation of orientation-selective units with peak sensitivity at the orientation of the adaptor (theta). Attractive (indirect) TAEs result from adaptation of second-stage units with peak sensitivity at theta and theta+90 degrees , which arise from an efficient stage of linear compression that pools across the responses of the first-stage orientation-selective units. A spatial orientation vector is estimated from the transformed oriented unit responses. The change from attractive to repulsive TAEs in peripheral vision can be explained by the differing harmonic biases resulting from constraints on signal power (in central vision) versus signal uncertainties in orientation (in peripheral vision). The proposed model is consistent with recent work by computational neuroscientists in supposing that visual bias reflects the adjustment of a rational system in the light of uncertain signals and system constraints.

The role of prior exposure on the capture of attention by items in working memory

The Biased Competition Model (BCM) suggests both top-down and bottom-up biases operate on selective attention (e.g., Desimone & Duncan, 1995). It has been suggested that top-down control signals may arise from working memory. In support, Downing (2000) found faster responses to probes presented in the location of stimuli held vs. not held in working memory. Soto, Heinke, Humphreys, and Blanco (2005) showed the involuntary nature of this effect and that shared features between stimuli were sufficient to attract attention. Here we show that stimuli held in working memory had an influence on the deployment of attentional resources even when: (1) It was detrimental to the task, (2) there was equal prior exposure, and (3) there was no bottom-up priming. These results provide further support for involuntary top-down guidance of attention from working memory and the basic tenets of the BCM, but further discredit the notion that bottom-up priming is necessary for the effect to occur.

Is gender a factor in perceived prison officer competence?

Background The introduction of women officers into HM Prison Service raised questions regarding women's ability to perform what had traditionally been a male role. Existing research is inconclusive as to whether female prison officers are as competent as male prison officers, and whether there are gender differences in job performance. This study examined prisoners' perceptions of male and female prison officers' performance. Hypotheses The hypotheses were that overall competence and professionalism ratings would not differ for men and women officers, but that there would be differences in how men and women were perceived to perform their roles. Women were expected to be rated as more communicative, more empathic and less disciplining. Method The Prison Officer Competency Rating Scale (PORS) was designed for this study. Ratings on the PORS for male and female officers were given by 57 adult male prisoners. Results There was no significant difference in prisoners' ratings of overall competence of men and women officers. Of the PORS subscales, there were no gender differences in Discipline and Control, Communication or Empathy, but there was a significant difference in Professionalism, where prisoners rated women as more professional. Conclusion The failure to find any differences between men and women in overall job competence, or on communication, empathy and discipline, as perceived by prisoners, suggests that men and women may be performing their jobs similarly in many respects. Women were rated as more professional, and items contributing to this scale related to respecting privacy and keeping calm in difficult situations, where there may be inherent gender biases. Copyright © 2005 Whurr Publishers Ltd.

Is subclinical thyroid dysfunction in the elderly associated with depression or cognitive dysfunction?

Background: Widespread use of automated sensitive assays for thyroid hormones and thyroid-stimulating hormone (TSH) has increased identification of mild thyroid dysfunction, especially in elderly patients. The clinical significance of this dysfunction, however, remains uncertain, and associations with cognitive impairment, depression, and anxiety are unconfirmed. Objective: To determine the association between mild thyroid dysfunction and cognition, depression, and anxiety in elderly persons. Design: Cross-sectional study. Associations were explored through mixed-model analyses. Setting: Primary care practices in central England. Patients: 5865 patients 65 years of age or older with no known thyroid disease who were recruited from primary care registers. Measurements: Serum TSH and free thyroxine (T4) were measured. Depression and anxiety were assessed by using the Hospital Anxiety and Depression Scale (HADS), and cognitive functioning was established by using the Middlesex Elderly Assessment of Mental State and the Folstein Mini-Mental State Examination. Comorbid conditions, medication use, and sociodemographic profiles were recorded. Results: 295 patients met the criteria for subclinical thyroid dysfunction (127 were hyperthyroid, and 168 were hypothyroid). After confounding variables were controlled for, statistically significant associations were seen between anxiety (HADS score) and TSH level (P = 0.013) and between cognition and both TSH and free T4 levels. The magnitude of these associations lacked clinical relevance: A 50-mIU/L increase in the TSH level was associated with a 1-point reduction in the HADS anxiety score, and a 1-point increase in the Mini-Mental State Examination score was associated with an increase of 50 mIU/L in the TSH level or 25 pmol/L in the free T4 level. Limitations: Because of the low participation rate, low prevalence of subclinical thyroid dysfunction, and other unidentified recruitment biases, participants may not be representative of the elderly population. Conclusions: After the confounding effects of comorbid conditions and use of medication were controlled for, subclinical thyroid dysfunction was not associated with depression, anxiety, or cognition. © 2006 American College of Physicians.

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

Applying quantitative methods in the assessment of outcomes of pharmacotherapy of psoriasis

Healthcare providers and policy makers are faced with an ever-increasing number of medical publications. Searching for relevant information and keeping up to date with new research findings remains a constant challenge. It has been widely acknowledged that narrative reviews of the literature are susceptible to several types of bias and a systematic approach may protect against these biases. The aim of this thesis was to apply quantitative methods in the assessment of outcomes of topical therapies for psoriasis. In particular, to systematically examine the comparative efficacy, tolerability and cost-effectiveness of topical calcipotriol in the treatment of mild-to-moderate psoriasis. Over the years, a wide range of techniques have been used to evaluate the severity of psoriasis and the outcomes from treatment. This lack of standardisation complicates the direct comparison of results and ultimately the pooling of outcomes from different clinical trials. There is a clear requirement for more comprehensive tools for measuring drug efficacy and disease severity in psoriasis. Ideally, the outcome measures need to be simple, relevant, practical, and widely applicable, and the instruments should be reliable, valid and responsive. The results of the meta-analysis reported herein show that calcipotriol is an effective antipsoriatic agent. In the short-tenn, the pooled data found calcipotriol to be more effective than calcitriol, tacalcitol, coal tar and short-contact dithranol. Only potent corticosteroids appeared to have comparable efficacy, with less short-term side-effects. Potent corticosteroids also added to the antipsoriatic effect of calcipotriol, and appeared to suppress the occurrence of calcipotriol-induced irritation. There was insufficient evidence to support any large effects in favour of improvements in efficacy when calcipotriol is used in combination with systemic therapies in patients with severe psoriasis. However, there was a total absence of long-term morbidity data on the effectiveness of any of the interventions studied. Decision analysis showed that, from the perspective of the NHS as payer, the relatively small differences in efficacy between calcipotriol and short-contact dithranol lead to large differences in the direct cost of treating patients with mildto-moderate plaque psoriasis. Further research is needed to examine the clinical and economic issues affecting patients under treatment for psoriasis in the UK. In particular, the maintenance value and cost/benefit ratio for the various treatment strategies, and the assessment of patient's preferences has not yet been adequately addressed for this chronic recurring disease.

Application of ERS-1 and Topex/Poseidon altimetry using precise orbits

The work described in this thesis concerns the application of radar altimetry, collected from the ERS-1 and TOPEX/POSEIDON missions, to precise satellite orbits computed at Aston University. The data is analysed in a long arc fashion to determine range biases, time tag biases, sea surface topographies and to assess the radial accuracy of the generated orbits through crossover analysis. A sea surface variability study is carried out for the North Sea using repeat altimeter profiles from ERS-1 and TOPEX/POSEIDON in order to verify two local U.K. models for ocean tide and storm surge effects. An on-side technique over the English Channel is performed to compute the ERS-1, TOPEX and POSEIDON altimeter range biases by using a combination of altimetry, precise orbits determined by short arc methods, tide gauge data, GPS measurements, geoid, ocean tide and storm surge models. The remaining part of the thesis presents some techniques for the short arc correction of long arc orbits. Validation of this model is achieved by way of comparison with actual SEASAT short arcs. Simulations are performed for the ERS-1 microwave tracking system, PRARE, using the range data to determine time dependent orbit corrections. Finally, a brief chapter is devoted to the recovery of errors in station coordinates by the use of multiple short arcs.

Orbit and altimetric corrections for the ERS satellites through analysis of single and dual satellite crossovers

Due to the failure of PRARE the orbital accuracy of ERS-1 is typically 10-15 cm radially as compared to 3-4cm for TOPEX/Poseidon. To gain the most from these simultaneous datasets it is necessary to improve the orbital accuracy of ERS-1 so that it is commensurate with that of TOPEX/Poseidon. For the integration of these two datasets it is also necessary to determine the altimeter and sea state biases for each of the satellites. Several models for the sea state bias of ERS-1 are considered by analysis of the ERS-1 single satellite crossovers. The model adopted consists of the sea state bias as a percentage of the significant wave height, namely 5.95%. The removal of ERS-1 orbit error and recovery of an ERS-1 - TOPEX/Poseidon relative bias are both achieved by analysis of dual crossover residuals. The gravitational field based radial orbit error is modelled by a finite Fourier expansion series with the dominant frequencies determined by analysis of the JGM-2 co-variance matrix. Periodic and secular terms to model the errors due to atmospheric density, solar radiation pressure and initial state vector mis-modelling are also solved for. Validation of the dataset unification consists of comparing the mean sea surface topographies and annual variabilities derived from both the corrected and uncorrected ERS-1 orbits with those derived from TOPEX/Poseidon. The global and regional geographically fixed/variable orbit errors are also analysed pre and post correction, and a significant reduction is noted. Finally the use of dual/single satellite crossovers and repeat pass data, for the calibration of ERS-2 with respect to ERS-1 and TOPEX/Poseidon is shown by calculating the ERS-1/2 sea state and relative biases.