Using Bad Learners to find Good Configurations

Finding the optimally performing configuration of a software system for a given setting is often challenging. Recent approaches address this challenge by learning performance models based on a sample set of configurations. However, building an accurate performance model can be very expensive (and is often infeasible in practice). The central insight of this paper is that exact performance values (e.g. the response time of a software system) are not required to rank configurations and to identify the optimal one. As shown by our experiments, models that are cheap to learn but inaccurate (with respect to the difference between actual and predicted performance) can still be used rank configurations and hence find the optimal configuration. This novel \emph{rank-based approach} allows us to significantly reduce the cost (in terms of number of measurements of sample configuration) as well as the time required to build models. We evaluate our approach with 21 scenarios based on 9 software systems and demonstrate that our approach is beneficial in 16 scenarios; for the remaining 5 scenarios, an accurate model can be built by using very few samples anyway, without the need for a rank-based approach.Comment: 11 pages, 11 figure

Scalable Bayesian nonparametric regression via a Plackett-Luce model for conditional ranks

We present a novel Bayesian nonparametric regression model for covariates X and continuous, real response variable Y. The model is parametrized in terms of marginal distributions for Y and X and a regression function which tunes the stochastic ordering of the conditional distributions F(y|x). By adopting an approximate composite likelihood approach, we show that the resulting posterior inference can be decoupled for the separate components of the model. This procedure can scale to very large datasets and allows for the use of standard, existing, software from Bayesian nonparametric density estimation and Plackett-Luce ranking estimation to be applied. As an illustration, we show an application of our approach to a US Census dataset, with over 1,300,000 data points and more than 100 covariates

Sequential projection pursuit for optimal transformation of autoregressive coefficients for damage detection in an experimental wind turbine blade

Peer reviewedPublisher PD

The public health risk posed by Listeria monocytogenes in frozen fruit and vegetables including herbs, blanched during processing

A multi-country outbreak ofListeria monocytogenesST6 linked to blanched frozen vegetables (bfV)took place in the EU (2015–2018). Evidence of food-borne outbreaks shows thatL. monocytogenesisthe most relevant pathogen associated with bfV. The probability of illness per serving of uncooked bfV,for the elderly (65–74 years old) population, is up to 3,600 times greater than cooked bfV and verylikely lower than any of the evaluated ready-to-eat food categories. The main factors affectingcontamination and growth ofL. monocytogenesin bfV during processing are the hygiene of the rawmaterials and process water; the hygienic conditions of the food processing environment (FPE); andthe time/Temperature (t/T) combinations used for storage and processing (e.g. blanching, cooling).Relevant factors after processing are the intrinsic characteristics of the bfV, the t/T combinations usedfor thawing and storage and subsequent cooking conditions, unless eaten uncooked. Analysis of thepossible control options suggests that application of a complete HACCP plan is either not possible orwould not further enhance food safety. Instead, specific prerequisite programmes (PRP) andoperational PRP activities should be applied such as cleaning and disinfection of the FPE, water control,t/T control and product information and consumer awareness. The occurrence of low levels ofL. monocytogenesat the end of the production process (e.g.<10 CFU/g) would be compatible with thelimit of 100 CFU/g at the moment of consumption if any labelling recommendations are strictly followed(i.e. 24 h at 5°C). Under reasonably foreseeable conditions of use (i.e. 48 h at 12°C),L. monocytogeneslevels need to be considerably lower (not detected in 25 g). Routine monitoring programmes forL. monocytogenesshould be designed following a risk-based approach and regularly revised based ontrend analysis, being FPE monitoring a key activity in the frozen vegetable industry