Principles of ‘Newspeak’ in Polish Translations of British and American Press Articles under Communist Rule

The paper analyses selected Polish translations of British and American press articles published in the magazine Forum in the years 1965 - 1989. In communist Poland, all such texts were censored before publication, which forced the translators to avoid content and language that could be banned by censors and to adopt a specific style of expression known as Newspeak. The paper lists the linguistic phenomena in the target language that represent features typical of Newspeak and identifies manipulative procedures which led to their occurrence, using a corpus of 25 English texts and their Polish translations

SoDeep: a Sorting Deep net to learn ranking loss surrogates

International audienceSeveral tasks in machine learning are evaluated using non-differentiable metrics such as mean average precision or Spearman correlation. However, their non-differentiability prevents from using them as objective functions in a learning framework. Surrogate and relaxation methods exist but tend to be specific to a given metric. In the present work, we introduce a new method to learn approximations of such non-differentiable objective functions. Our approach is based on a deep architecture that approximates the sorting of arbitrary sets of scores. It is trained virtually for free using synthetic data. This sorting deep (SoDeep) net can then be combined in a plug-and-play manner with existing deep architectures. We demonstrate the interest of our approach in three different tasks that require ranking: Cross-modal text-image retrieval, multi-label image classification and visual memorability ranking. Our approach yields very competitive results on these three tasks, which validates the merit and the flexibility of SoDeep as a proxy for sorting operation in ranking-based losses

From the Visions of Saint Teresa of Jesus to the Voices of Schizophrenia

The life of Saint Teresa of Jesus, the most famous mystic of sixteenth-century Spain, was characterized by recurrent visions and states of ecstasy. In this paper, we examine social components related to Teresa’s personal crises and the historical conditions of her times, factors that must be taken into account to understand these unusual forms of experience and behavior. Many of these factors (e.g., increasing individualism and reflexivity) are precursors of the condition of modern times. Indeed, certain parallels can be observed between Saint Teresa and certain present-day psychopathological disorders. The analogy should not, however, be carried too far. Religion played a particularly crucial role in Teresa’s cultural context; as a result, it would be misleading to view her mystical experiences as resulting from a mental disorder

Double-descent curves in neural networks: a new perspective using Gaussian processes

Double-descent curves in neural networks describe the phenomenon that the generalisation error initially descends with increasing parameters, then grows after reaching an optimal number of parameters which is less than the number of data points, but then descends again in the overparameterised regime. Here we use a neural network Gaussian process (NNGP) which maps exactly to a fully connected network (FCN) in the infinite width limit, combined with techniques from random matrix theory, to calculate this generalisation behaviour, with a particular focus on the overparameterised regime. An advantage of our NNGP approach is that the analytical calculations are easier to interpret. We argue that neural network generalization performance improves in the overparameterised regime precisely because that is where they converge to their equivalent Gaussian process