Off-the-grid: Fast and Effective Hyperparameter Search for Kernel Clustering

Kernel functions are a powerful tool to enhance the $k$-means clustering algorithm via the kernel trick. It is known that the parameters of the chosen kernel function can have a dramatic impact on the result. In supervised settings, these can be tuned via cross-validation, but for clustering this is not straightforward and heuristics are usually employed. In this paper we study the impact of kernel parameters on kernel $k$-means. In particular, we derive a lower bound, tight up to constant factors, below which the parameter of the RBF kernel will render kernel $k$-means meaningless. We argue that grid search can be ineffective for hyperparameter search in this context and propose an alternative algorithm for this purpose. In addition, we offer an efficient implementation based on fast approximate exponentiation with provable quality guarantees. Our experimental results demonstrate the ability of our method to efficiently reveal a rich and useful set of hyperparameter values.Comment: ECML-PKDD 202

Mobile apps use and WOM in the food delivery sector: The role of planned behavior, perceived security and customer lifestyle compatibility

This research examines the phenomenon of food delivery services fromthe mobile app user''s perspective and how consumers'' lifestyles are changing because of the convenience provided by the apps. By means of an online survey targeted at US food delivery app customers, our study analyzes the main motivations that lead them to use and recommend these technology-based services. The results of the study revealed that some of the theory of planned behavior model variables (i.e., attitude toward the behavior, subjective norms), influence customer use and word-of-mouth (WOM) intentions. Security influences intention to spread WOM, whereas customer lifestyle compatibility influences intention to use the food delivery apps. A post hoc analysis revealed that perceived control is only important for older customers, who need to perceive that they control the apps before they will recommend them to other customers. The findings of the study are discussed and contrasted with previous research in the field. The managerial implications derived from the findings provide practical guidance for food delivery app companies. Further research avenues are suggested to encourage scholars to continue investigating the challenge of the diffusion of mobile apps in the food delivery and related sectors

A multi-stakeholder participatory study identifies the priorities for the sustainability of the small ruminants farming sector in Europe

The European small ruminants (i.e. sheep and goats) farming sector (ESRS) provides economic, social and environmental benefits to society, but is also one of the most vulnerable livestock sectors in Europe. This sector has diverse livestock species, breeds, production systems and products, which makes difficult to have a clear vision of its challenges through using conventional analyses. A multi-stakeholder and multi-step approach, including 90 surveys, was used to identify and assess the main challenges for the sustainability of the ESRS to prioritize actions. These challenges and actions were identified by ESRS experts including farmers, cooperatives, breeding associations, advisers and researchers of six EU countries and Turkey. From the 30 identified challenges, the most relevant were economy-related challenges such as ‘uncertainty of meat and milk prices’, ‘volatility of commodity prices’, ‘low farm income’, ‘high subsidy dependency’ and ‘uncertainty in future changes in subsidies’ resulting in ‘a sector not attractive to young farmers’. Most of these challenges were beyond the farmer''s control and perceived as difficult to address. Challenges were prioritized using an index, calculated by multiplying the relevance and the feasibility to address measures. The identified challenges had a similar priority index across the whole sector with small differences across livestock species (sheep vs goats), type of products (meat vs dairy) and intensification levels (intensive vs semi-intensive vs extensive). The priorities were different, however, between socio-geographical regions (Southern vs Central Europe). Some of the top prioritized challenges were linked to aspects related to the production systems (‘low promotion of local breeds’ and ‘slow adaptability of high producing breeds’) and market practices (‘unfair trade/lack of traceability’). The majority of the priority challenges, however, were associated with a deficient knowledge or training at farm level (‘poor business management training’, ‘lack of professionalization’, ‘slow adoption of innovations’), academia (‘researchers do not address real problems’) and society as a whole (‘low consumer education in local products’, ‘low social knowledge about farming’, ‘poor recognition of farming public services’). Thus, improved collaboration among the different stakeholders across the food chain with special implication of farmers, associations of producers, academia and governments is needed to facilitate knowledge exchange and capacity building. These actions can contribute to make ESRS economically more sustainable and to adapt the production systems and policy to the current and future societal needs in a more region-contextualized framework