The Feature in Radio – the Elusiveness of the Genre’s Determinants. Notes on the Prix Europa Festival in the Years 2012 and 2013 in the Context of Literary Genetics

The goal of the article is to answer the question: what do radio broadcasters in the West understand to be a ‘feature’? A lack of clarity in terminology in this respect was especially visible during the Prix Europa 2012 and 2013 festivals. The article begins with an outline of the term ‘feature’, followed by discussion of relevant festival categories, and ending with a presentation of several selected audio examples that indicate both the characteristics of the genre and cases where, in spite of divergences from these qualities, the term ‘feature’ continues to function.Zadanie „Stworzenie anglojęzycznych wersji wydawanych publikacji” finansowane w ramach umowy nr 948/P-DUN/2016 ze środków Ministra Nauki i Szkolnictwa Wyższego przeznaczonych na działalność upowszechniającą naukę

An architecture for life-long user modelling

In this paper, we propose a united architecture for the creation of life-long user profiles. Our architecture combines different steps required for a user prole, including feature extraction and representation, reasoning, recommendation and presentation. We discuss various issues that arise in the context of life-long profiling

Modelling and analysing user views of telecommunications services

User views of calls are modelled by behaviour trees, which are synchronised to form a network of users. High level presentations of the models are given using process algebra and an explicit theory of features, including precedences. These precedences abstractly encapsulate the possible state spaces which result from different combinations of features. The high level presentation supports incremental development of features and testing and experimentation through animation. Interactions which are not detected during the experimentation phase may be found through static analysis of the high level presentation, through dynamic analysis of the under-lying low level transition system, and through verification of temporal properties through model-checking. In each case, interactions are resolved through manipulation of the feature precedences

Understanding Learned Models by Identifying Important Features at the Right Resolution

In many application domains, it is important to characterize how complex learned models make their decisions across the distribution of instances. One way to do this is to identify the features and interactions among them that contribute to a model's predictive accuracy. We present a model-agnostic approach to this task that makes the following specific contributions. Our approach (i) tests feature groups, in addition to base features, and tries to determine the level of resolution at which important features can be determined, (ii) uses hypothesis testing to rigorously assess the effect of each feature on the model's loss, (iii) employs a hierarchical approach to control the false discovery rate when testing feature groups and individual base features for importance, and (iv) uses hypothesis testing to identify important interactions among features and feature groups. We evaluate our approach by analyzing random forest and LSTM neural network models learned in two challenging biomedical applications.Comment: First two authors contributed equally to this work, Accepted for presentation at the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19

Two-Dimensional Self-Consistent Quantum-Corrected Geometries with a Constant Dilaton Feld

It is argued that the existence of constant dilaton field solutions is a generic feature of string-inspired dilaton gravity. Such solutins arise in the extreme limit of black hole metrics. It is shown that in a strong coupling region quantum effects give rise to two horizons in thermal equilibrium that has no classical counterpart.Comment: 7 pages, REVTeX, no figures. Minor corrections in presentation. To be published in Phys. Lett.