Generalization from correlated sets of patterns in the perceptron

Generalization is a central aspect of learning theory. Here, we propose a framework that explores an auxiliary task-dependent notion of generalization, and attempts to quantitatively answer the following question: given two sets of patterns with a given degree of dissimilarity, how easily will a network be able to "unify" their interpretation? This is quantified by the volume of the configurations of synaptic weights that classify the two sets in a similar manner. To show the applicability of our idea in a concrete setting, we compute this quantity for the perceptron, a simple binary classifier, using the classical statistical physics approach in the replica-symmetric ansatz. In this case, we show how an analytical expression measures the "distance-based capacity", the maximum load of patterns sustainable by the network, at fixed dissimilarity between patterns and fixed allowed number of errors. This curve indicates that generalization is possible at any distance, but with decreasing capacity. We propose that a distance-based definition of generalization may be useful in numerical experiments with real-world neural networks, and to explore computationally sub-dominant sets of synaptic solutions

Using machine-learning modelling to understand macroscopic dynamics in a system of coupled maps

Machine learning techniques not only offer efficient tools for modelling dynamical systems from data, but can also be employed as frontline investigative instruments for the underlying physics. Nontrivial information about the original dynamics, which would otherwise require sophisticated ad-hoc techniques, can be obtained by a careful usage of such methods. To illustrate this point, we consider as a case study the macroscopic motion emerging from a system of globally coupled maps. We build a coarse-grained Markov process for the macroscopic dynamics both with a machine learning approach and with a direct numerical computation of the transition probability of the coarse-grained process, and we compare the outcomes of the two analyses. Our purpose is twofold: on the one hand, we want to test the ability of the stochastic machine learning approach to describe nontrivial evolution laws, as the one considered in our study; on the other hand, we aim at gaining some insight into the physics of the macroscopic dynamics by modulating the information available to the network, we are able to infer important information about the effective dimension of the attractor, the persistence of memory effects and the multi-scale structure of the dynamics.Comment: 17 pages, 13 figure

ESA ESRIN'S VALUE FOR ITALY

The report presents an overview of the evolution of ESA's ESRIN stablishment. The programs and activities carried out by ESRIN are then analyzed, with particular attention to the Earth Observation and VEGA programs. We then moved on to assessing the economic and strategic impact of ESRIN for Italy. In particular, an estimate was made of the direct and indirect economic impact and of the scientific value developed by ESRIN on the Italian territory

Sustainability for Food Consumers: Which Perception?

A sustainable future for the community is one of the objectives established by the European Union Agenda 2030. Furthermore, sustainable consumption has been identified as one of the possible trajectories for sustainable development. It is for this reason that food production, distribution and consumption ways cannot be overlooked for sustainability achievement, as well as the consumer’s related perception. In this research the Best–Worst scaling methodology was adopted to explore the priorities declared by a sample of 801 consumers among 12 different sustainability definitions selected from the scientific literature. The choice experiment was carried out through face-to-face interviews during two food and wine events closely related to the sustainability theme in the food sector. The respondents considered as sustainability priority definition the “preservation of natural resources”, followed by “decent working conditions” and “accessibility for everyone to healthy and safe food”. Moreover, 5 consumer’s clusters were identified according to the priorities assigned to the different sustainability definitions, as well as to individuals socio-demographic characteristics. The description of the priorities assigned by the clusters to the different sustainability definitions have also been described as guidelines for consumer attitudes towards the different sustainability dimensions (environmental, social, economic and governance)

Consumer Attitudes and Preference Exploration towards Fresh-Cut Salads Using Best–Worst Scaling and Latent Class Analysis

This research explored the preferences and buying habits of a sample of 620 consumers of fresh-cut, ready-to-eat salads. A best–worst scaling approach was used to measure the level of preference stated by individuals regarding 12 attributes for quality (intrinsic, extrinsic and credence) of fresh-cut salads. The experiment was carried out through direct interviews at several large-scale retail outlets in the Turin metropolitan area (north-west of Italy). Out of the total number of questioned consumers, 35% said they did not consume fresh-cut salads. On the contrary, the rest of the involved sample expressed the highest degree of preference towards the freshness/appearance attribute, followed by the expiration date and the brand. On the contrary, attributes such as price, organic certification and food safety did not emerge as discriminating factors in consumer choices. Additionally, five clusters of consumers were identified, whose preferences are related both to purchasing styles and socio-demographic variables. In conclusion, this research has highlighted the positive attitude of consumers towards quality products backed by a brand, providing ideas for companies to improve within this sector and implement strategies to answer the needs of a new segment of consumers, by determining market opportunities that aim to strengthen local brands

Consumption vs. non-consumption of plant-based beverages : a case study on factors influencing consumers' choices

Plant-based beverages (PBBs) represent a growing global alternative to cow's milk. However, their development is strongly influenced by consumers’ expectations of new foods introduced into the diet: environmental sustainability, balanced nutritional content, health aspects, and organoleptic properties. This study analyzes consumers' preferences and choice orientations towards plant-based beverages through the assessment of their eating style and concern towards environmental and health issues. To that end, an online questionnaire was conducted with a sample of 233 respondents living in the South-East area of Italy. Initially, principal component analyses were performed to identify distinct dimensions of individuals' orientation towards food quality, environment and health involvement. Then, the emerging dimensions were used as dependent variables for ANOVA comparisons between consumers and non-consumers of plant-based beverages, considering also individuals’ preferences towards different PBBs. The main results showed a strong consumer concern for environmental sustainability issues, which was found as the main purchasing driver for plant-based beverage consumers. On the other hand, many respondents stated that they do not consume PBBs due to their negative organoleptic aspects and the unfamiliarity with these products. Furthermore, the individual's dietary style influences the consumption of plant-based beverages and, in particular, the search for nutritional and balanced compounds plays a key role in consumption choices. Finally, despite that the almonds cultivation for the traditional 'almond milk' production is typical in various Italian regions, consumers expressed averagely a weak connection with this product. In conclusion, considering our results, the market development of PPBs at a national level might be supported by marketing strategies dedicated to different individuals’ profiles. At the same time, however, direct actions on the production process are needed to improve the organoleptic profile of these products and meet the dissatisfaction expressed by consumers