Learning the learning rate for prediction with expert advice

Most standard algorithms for prediction with expert advice depend on a parameter called the learning rate. This learning rate needs to be large enough to fit the data well, but small enough to prevent overfitting. For the exponential weights algorithm, a sequence of prior work has established theoretical guarantees for higher and higher data-dependent tunings of the learning rate, which allow for increasingly aggressive learning. But in practice such theoretical tunings often still perform worse (as measured by their regret) than ad hoc tuning with an even higher learning rate. To close the gap between theory and practice we introduce an approach to learn the learning rate. Up to a factor that is at most (poly)logarithmic in the number of experts and the inverse of the learning rate, our method performs as well as if we would know the empirically best learning rate from a large range that includes both conservative small values and values that are much higher than those for which formal guarantees were previously available. Our method employs a grid of learning rates, yet runs in linear time regardless of the size of the grid.

Prior and posterior linear pooling for combining expert opinions: Uses and impact on Bayesian Networks

The use of expert knowledge to quantify a Bayesian Network (BN) is necessary when data is not available. This however raises questions regarding how opinions from multiple experts can be used in a BN. Linear pooling is a popular method for combining probability assessments from multiple experts. In particular, Prior Linear Pooling (PrLP), which pools opinions then places them into the BN is a common method. This paper firstly proposes an alternative pooling method, Posterior Linear Pooling (PoLP). This method constructs a BN for each expert, then pools the resulting probabilities at the nodes of interest. Secondly, it investigates the advantages and disadvantages of using these pooling methods to combine the opinions of multiple experts. Finally, the methods are applied to an existing BN, the Wayfinding Bayesian Network Model, to investigate the behaviour of different groups of people and how these different methods may be able to capture such differences. The paper focusses on 6 nodes Human Factors, Environmental Factors, Wayfinding, Communication, Visual Elements of Communication and Navigation Pathway, and three subgroups Gender (female, male),Travel Experience (experienced, inexperienced), and Travel Purpose (business, personal) and finds that different behaviors can indeed be captured by the different methods.

Adapting to concurrent expert evidence in medical litigation

In medical negligence litigation expert evidence has long played a dominant role. The trend towards the use of concurrent expert evidence is now well underway. However, for the lawyers and the doctors involved, the pathway is not yet familiar. Disputes have frequently arisen in the context of pre-hearing expert conclaves, given the adversarial nature of litigation and perhaps fuelled by fears of a less transparent process at this increasingly important stage. This article explains the concurrent expert evidence framework and examines areas of common dispute both in the conclaves and at trial, with a view to providing assistance to legal practitioners working in this area and the medical practitioners called upon to provide expert evidence in such litigation.

Global standard for the composition of infant formula: Recommendations of an ESPGHAN coordinated international expert group

The Codex Alimentarius Commission of the Food and Agriculture Organization of the United Nations (FAO) and the World Health Organization (WHO) develops food standards, guidelines and related texts for protecting consumer health and ensuring fair trade practices globally. The major part of the world's population lives in more than 160 countries that are members of the Codex Alimentarius. The Codex Standard on Infant Formula was adopted in 1981 based on scientific knowledge available in the 1970s and is currently being revised. As part of this process, the Codex Committee on Nutrition and Foods for Special Dietary Uses asked the ESPGHAN Committee on Nutrition to initiate a consultation process with the international scientific community to provide a proposal on nutrient levels in infant formulae, based on scientific analysis and taking into account existing scientific reports on the subject. ESPGHAN accepted the request and, in collaboration with its sister societies in the Federation of International Societies on Pediatric Gastroenterology, Hepatology and Nutrition, invited highly qualified experts in the area of infant nutrition to form an International Expert Group (IEG) to review the issues raised. The group arrived at recommendations on the compositional requirements for a global infant formula standard which are reported here.

Assessing performance in critical care nursing practice using the Benner Novice to expert model: A pilot study

Background It is often believed that by ensuring the ongoing completion of competency documents and life-long learning in nursing practice guarantees quality patient care. This is probably true in most cases where it provides reassurances that the nursing team is maintaining a safe “generalised” level of practice. However, competency does not always promise quality performance. There are a number of studies that have reported differences in what practitioners know and what they actually do despite being deemed competent. Aim The aim of this study was to assess whether our current competency documentation is fit for purpose and to ascertain whether performance assessment needs to be a key component in determining competence. Method 15 nurses within a General ICU who had been on the unit <4 years agreed to participate in this project. Using participant observation and assessing performance against key indicators of the Benner Novice to Expert5 model the participants were supported and assessed over the course of a ‘normal’ nursing shift. Results The results were surprising both positively and negatively. First, the nurses felt more empowered in their clinical decision making skills; second, it identified individual learning needs and milestones in educational development. There were some key challenges identified which included 5 nurses over estimating their level of competence, practice was still very much focused on task acquisition and skill and surprisingly some nurses still felt dominated by the other health professionals within the unit. Conclusion We found that the capacity and capabilities of our nursing workforce needs continual ongoing support especially if we want to move our staff from capable task-doer to competent performers. Using the key novice to expert indicators identified the way forward for us in how we assess performance and competence in practice particularly where promotion to higher grades is based on existing documentation.

Eliciting and encoding expert knowledge on variable selection into classical or Bayesian species distribution models

The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.

Conclaves and concurrent expert evidence: A positive development in Australian legal practice?

Many Australian courts now prefer pre-hearing meetings of experts (conclaves) being convened to prepare joint reports to identify areas of agreement and disagreement, followed by concurrent expert evidence at trial. This contrasts to the traditional approach where experts did not meet before trial and did not give evidence together. Most judges, lawyers and expert witnesses favour this as a positive development in Australian legal practice, at least for civil disputes. This new approach impacts medical practitioners who are called upon to give expert evidence, or who are parties to disputes before the courts. Arguably, it is too soon to tell whether the relative lack of transparency at the conclave stage will give rise to difficulties in the coronial, disciplinary and criminal arenas.

Honesty in the provision of expert services: The effect of naturalistic framings and participants' professions

This thesis studies the incentives and behaviour of providers of expert services, like doctors, financial advisors and mechanics. The focus is in particular on provision of health care using a series of credence goods experiments conducted to investigate undertreatment, overtreatment and overcharging in a medical context. The findings of study one suggest that a medical framing compared to a neutral framing significantly increases pro-social behaviour for standard participants in economic experiments. Study two compares the behaviour of medical practitioners - mainly doctors - to students. It is observed that medical doctors’ undertreat and overcharge significantly less, but at the same time overtreat significantly more than students. The final study compares behaviours for other experts - accountants, engineers and lawyers - using experimental framings drawn from the respective contexts and students from the respective faculties as participants in credence goods experiments.

Promoting and providing expert guidance in work-intensive clinical settings

This paper discusses how expert guidance can be best provided in work intensive clinical settings. The adequacy for supporting learning in the clinical practicum for health care disciplines is often complicated by the intensive work practices in healthcare settings. Often, clinicians' work is so intense that the scope for providing close guidance for students is quite restricted. The case advanced here draws on a range of empirical work to propose how clinician-student interactions might be optimized through the provision of a clinical ccn guided learning such as demonstrating and role-modeling. These roles can contribute in essential ways to the development of learning environments where clinicians have the opportunity to facilitate the learning of others as part of their workload, and without being burdened by the requirements of teaching and assessment processes. It differs from other approaches because although clinicians partner students and provide feedback to them, clinicians are not expected to formally assess or award a grade for student performance. Assessment and remedial action, when required, is undertaken by the role of a designated clinical supervisor qualified to perform such activities. © 2010 Springer Science+Business Media B.V.

Integrating science through Bayesian Belief Networks : case study of Lyngbya in Moreton Bay

Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex ecological problems. In a BBN, the important variables in a problem are identified and causal relationships are represented graphically. Underpinning this is the probabilistic framework in which variables can take on a finite range of mutually exclusive states. Associated with each variable is a conditional probability table (CPT), showing the probability of a variable attaining each of its possible states conditioned on all possible combinations of it parents. Whilst the variables (nodes) are connected, the CPT attached to each node can be quantified independently. This allows each variable to be populated with the best data available, including expert opinion, simulation results or observed data. It also allows the information to be easily updated as better data become available ----- ----- This paper reports on the process of developing a BBN to better understand the initial rapid growth phase (initiation) of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay, Queensland. Anecdotal evidence suggests that Lyngbya blooms in this region have increased in severity and extent over the past decade. Lyngbya has been associated with acute dermatitis and a range of other health problems in humans. Blooms have been linked to ecosystem degradation and have also damaged commercial and recreational fisheries. However, the causes of blooms are as yet poorly understood.

Neonatal palliative care attitude scale : development of an instrument to measure the barriers to and facilitators of palliative care in neonatal nursing

OBJECTIVE The aim of this research project was to obtain an understanding of the barriers to and facilitators of providing palliative care in neonatal nursing. This article reports the first phase of this research: to develop and administer an instrument to measure the attitudes of neonatal nurses to palliative care. METHODS The instrument developed for this research (the Neonatal Palliative Care Attitude Scale) underwent face and content validity testing with an expert panel and was pilot tested to establish temporal stability. It was then administered to a population sample of 1285 neonatal nurses in Australian NICUs, with a response rate of 50% (N 645). Exploratory factor-analysis techniques were conducted to identify scales and subscales of the instrument. RESULTS Data-reduction techniques using principal components analysis were used. Using the criteria of eigenvalues being 1, the items in the Neonatal Palliative Care Attitude Scale extracted 6 factors, which accounted for 48.1% of the variance among the items. By further examining the questions within each factor and the Cronbach’s of items loading on each factor, factors were accepted or rejected. This resulted in acceptance of 3 factors indicating the barriers to and facilitators of palliative care practice. The constructs represented by these factors indicated barriers to and facilitators of palliative care practice relating to (1) the organization in which the nurse practices, (2) the available resources to support a palliative model of care, and (3) the technological imperatives and parental demands. CONCLUSIONS The subscales identified by this analysis identified items that measured both barriers to and facilitators of palliative care practice in neonatal nursing. While establishing preliminary reliability of the instrument by using exploratory factor-analysis techniques, further testing of this instrument with different samples of neonatal nurses is necessary using a confirmatory factor-analysis approach.

Research Monograph: The role of community and lifestyle in the making of a knowledge city

Our brief is to investigate the role of community and lifestyle in the making of a globally successful knowledge city region. Our approach is essentially pragmatic. We start by broadly examining knowledge-based urban development from a number of different perspectives. The first view is historical. In this context knowledge work and knowledge workers are seen as vital parts of a new emergent mode of production reliant on the continual production of abstract knowledge. We briefly develop this perspective to encompass the work of Richard Florida who has, notedly, claimed: “Wherever talent goes, innovation, creativity, and economic growth are sure to follow.” Our next perspective examines concepts of knowledge and modes of its production to discover knowledge is not an unchanging object but a human activity that changes in form and content through history. The suggestion emerges that not only is the production of contemporary ‘knowledge’ organised in a specific (and new) manner but also the output of this networked production is a particular type of knowledge (i.e. techné). The third perspective locates knowledge production and its workers in the contemporary urban context. As such, it co-ordinates the knowledge city in the increasingly global structure of cities and develops a typology of different groups of knowledge workers in their preferred urban environment(s). We see emerging here a distinctive geography of knowledge production. It is an urban phenomenon. There is, in short, something about the nature of cities that knowledge workers find particularly attractive. In the next, essentially anthropological, perspective we start to explore the needs and desires of the individual knowledge worker. Beyond the needs basic to any modern human household an attempt is made to deduce, from a base understanding of knowledge work as mental labour, the compensatory cultural needs of the knowledge worker when not at work - and the expression of these needs in the urban fabric. Our final perspective consists of two case studies. In a review of the experiences of Austin, Texas and Singapore’s one-north precinct we collect empirical data on, respectively, a knowledge city that has sustained itself for over 50 years and an urban precinct newly launched into the global market for knowledge work and knowledge workers. Interwoven The Role of Community and Lifestyle in the Making of a Knowledge City Urban Research Program 8 through all perspectives, in the form of apposite citation, is that of ‘expert opinion’ gathered in a rudimentary poll of academic and industry sources. This opinion appears in text boxes while details of the survey can be found in Appendix A. In the conclusion of the report we interpret the wide range of evidence gathered above in a policy frame. It is our hope this report will leave the reader with a clearer picture of the decisive organisational, infrastructural, aesthetic and social dimensions of a knowledge precinct.