Preference-based Search using Example-Critiquing with Suggestions

We consider interactive tools that help users search for their most preferred item in a large collection of options. In particular, we examine example-critiquing, a technique for enabling users to incrementally construct preference models by critiquing example options that are presented to them. We present novel techniques for improving the example-critiquing technology by adding suggestions to its displayed options. Such suggestions are calculated based on an analysis of users current preference model and their potential hidden preferences. We evaluate the performance of our model-based suggestion techniques with both synthetic and real users. Results show that such suggestions are highly attractive to users and can stimulate them to express more preferences to improve the chance of identifying their most preferred item by up to 78%

Simultaneous Elicitation of Committee and Voters' Preferences

Co-localisées avec la Plate-Forme Intelligence Artificielle (PFIA 2019)International audienceSocial choice deals with the problem of determining a consensus choice from the preferences of different voters. In the classical setting, the voting rule is fixed beforehand and full information concerning he preferences of the voters is provided. Recently, the assumption of full preference information has been questioned by a number of researchers and several methods for eliciting preferences have been proposed. In this paper we go one step further and we assume that both the voting rule and the voters’ preferences are partially specified. In this setting, we present an interactive elicitation protocol based on minimax regret and develop several query strategies that interleave questions to the chair and questions to the voters in order to attempt to acquire the most relevant information in order to quickly converge to optimal or a near-optimal alternative

A Comparative Analysis of Deterministic Detection and Estimation Techniques for MIMO SFCW Radars

In this paper, the problem of the joint estimation of the range and azimuth of multiple targets in a multiple-input multiple-output stepped-frequency continuous wave radar system is investigated. Three deterministic algorithms solving it through an iterative beam cancellation procedure are described; moreover, an iterative technique, based on the expectation-maximization algorithm, is developed with the aim of refining their estimates. The accuracy achieved by all the considered algorithms is assessed on the basis of the raw data acquired from a low power wideband radar device. Our results evidence that these algorithms achieve similar accuracies, but at the price of different computational efforts

photosensitizing proteins for antibacterial photodynamic inactivation

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Difference in PaO2/FiO2 between high-flow nasal cannula and Venturi mask in hypoxemic COVID-19 patients

The ratio between arterial blood partial pressure of oxygen and fraction of inspired oxygen (PaO2/FiO2) was largely used for grading and managing the respiratory failure in non-mechanically ventilated COVID-19. In these patients, the assessment of the true FiO2 in the inspired mixture may be difficult with consequent inaccuracies in PaO2/FiO2 assessment. In 30 severe COVID-19 patients, we observed that PaO2/FiO2 values measured immediately before and after the transition from high-flow nasal cannula (HFNC) to one commercially available Venturi mask O2 therapy were similar (bias mean value 0, standard deviation 23 mmHg). In COVID-19 patients recovering from respiratory failure, PaO2/FiO2 is not different whether measured with a commercially available Venturi mask or HFNC

Targeted photoimmunotherapy for cancer

Photodynamic therapy (PDT) is a clinically approved procedure that can exert a curative action against malignant cells. The treatment implies the administration of a photoactive molecular species that, upon absorption of visible or near infrared light, sensitizes the formation of reactive oxygen species. These species are cytotoxic and lead to tumor cell death, damage vasculature, and induce inflammation. Clinical investigations demonstrated that PDT is curative and does not compromise other treatment options. One of the major limitations of the original method was the low selectivity of the photoactive compounds for malignant over healthy tissues. The development of conjugates with antibodies has endowed photosensitizing molecules with targeting capability, so that the compounds are delivered with unprecedented precision to the site of action. Given their fluorescence emission capability, these supramolecular species are intrinsically theranostic agents

Efficient exact computation of setwise minimax regret for interactive preference elicitation

A key issue in artificial intelligence methods for interactive preference elicitation is choosing at each stage an appropriate query to the user, in order to find a near-optimal solution as quickly as possible. A theoretically attractive method is to choose a query that minimises max setwise regret (which corresponds to the worst case loss response in terms of value of information). We focus here on the situation in which the choices are represented explicitly in a database, and with a model of user utility as a weighted sum of the criteria; in this case when the user makes a choice, an agent learns a linear constraint on the unknown vector of weights. We develop an algorithmic method for computing minimax setwise regret for this form of preference model, by making use of a SAT solver with cardinality constraints to prune the search space, and computing max setwise regret using an extreme points method. Our experimental results demonstrate the feasibility of the approach and the very substantial speed up over the state of the art