A Comparative Study of Ranking-based Semantics for Abstract Argumentation

Argumentation is a process of evaluating and comparing a set of arguments. A way to compare them consists in using a ranking-based semantics which rank-order arguments from the most to the least acceptable ones. Recently, a number of such semantics have been proposed independently, often associated with some desirable properties. However, there is no comparative study which takes a broader perspective. This is what we propose in this work. We provide a general comparison of all these semantics with respect to the proposed properties. That allows to underline the differences of behavior between the existing semantics.Comment: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-2016), Feb 2016, Phoenix, United State

Big Tobacco, Alcohol, and Food and NCDs in LMICs: An Inconvenient Truth and Call to Action; Comment on “Addressing NCDs: Challenges From Industry Market Promotion and Interferences”

In their editorial, Tangcharoensathien et al1 describe the challenges of industry market promotion and policy interference from Big Tobacco, Alcohol, and Food in addressing non-communicable diseases (NCDs). They provide an overview of the increasing influence of corporate interest in emerging economies and government attempts to implement the World Health Organization (WHO) ‘best buy’ interventions. The authors largely draw on examples from Asia and a few selected countries, but provide little detail as to how aggressive marketing and policy interference plays out in a context of poor legislation and regulation in many low- and middle-income countries (LMICs), where the burden of NCDs is increasing at an alarming rate and governments face a high burden of disease with a limited budget for countering industry interference. This commentary provides some poignant examples of the influence of Big Tobacco, Alcohol, and Food on market regulation and policy interference in LMICs and argues for more policy coherence and accountability in terms of multisectoral action and civil society activism. Securing funds for health promotion and establishing health promotion foundations could help achieve that goal

FairDistillation: Mitigating Stereotyping in Language Models

Large pre-trained language models are successfully being used in a variety of tasks, across many languages. With this ever-increasing usage, the risk of harmful side effects also rises, for example by reproducing and reinforcing stereotypes. However, detecting and mitigating these harms is difficult to do in general and becomes computationally expensive when tackling multiple languages or when considering different biases. To address this, we present FairDistillation: a cross-lingual method based on knowledge distillation to construct smaller language models while controlling for specific biases. We found that our distillation method does not negatively affect the downstream performance on most tasks and successfully mitigates stereotyping and representational harms. We demonstrate that FairDistillation can create fairer language models at a considerably lower cost than alternative approaches.Comment: Accepted at ECML-PKDD 202

Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning

Machine learning is being integrated into a growing number of critical systems with far-reaching impacts on society. Unexpected behaviour and unfair decision processes are coming under increasing scrutiny due to this widespread use and its theoretical considerations. Individuals, as well as organisations, notice, test, and criticize unfair results to hold model designers and deployers accountable. We offer a framework that assists these groups in mitigating unfair representations stemming from the training datasets. Our framework relies on two inter-operating adversaries to improve fairness. First, a model is trained with the goal of preventing the guessing of protected attributes' values while limiting utility losses. This first step optimizes the model's parameters for fairness. Second, the framework leverages evasion attacks from adversarial machine learning to generate new examples that will be misclassified. These new examples are then used to retrain and improve the model in the first step. These two steps are iteratively applied until a significant improvement in fairness is obtained. We evaluated our framework on well-studied datasets in the fairness literature -- including COMPAS -- where it can surpass other approaches concerning demographic parity, equality of opportunity and also the model's utility. We also illustrate our findings on the subtle difficulties when mitigating unfairness and highlight how our framework can assist model designers.Comment: 15 pages, 3 figures, 1 tabl

Crassicauda boopis in a fin whale (Balaenoptera physalus) ship-struck in the eastern North Atlantic Ocean

On 9 November 2015, a juvenile male fin whale of 11·60 m length was observed on the bulb of a merchant vessel in the Channel Terneuzen – Ghent (The Netherlands – Belgium). A severe parasitosis was present in the right heart ventricle and caudal caval vein. Parasites were identified as Crassicauda boopis based on macroscopic and microscopic observations. The sequence of the 18S rRNA gene obtained from the parasite samples was 100% similar to the sequence of the 18S rRNA gene from Crassicauda magna available on GenBank. While adults of C. boopis and C. magna are morphologically distinct and found at different locations in the body, the molecular analysis of the 18S rRNA gene seems insufficient for reliable species identification. Although numerous C. boopis were found, the cause of death was identified as due to the collision with the ship, as suggested by the presence of a large haematoma, and the absence of evidence of renal failure. The young age of this whale and the absence of severe chronic reaction may suggest that the infestation was not yet at an advanced chronic stage

Heat Estimation from Infrared Measurement Compared to DSC for Austenite to R Phase Transformation in a NiTi Alloy

International audienceHeat sources estimations from temperature field measurements deduced from infrared imaging are increasingly used to study thermo-mechanical coupling during materials deformation. These estimations are based on approximations of the derivative terms with respect to time and space which are involved in the heat diffusion equation. This paper proposes a first experimental validation of this method by applying it to an experimental uniform air cooling of a NiTi Shape Memory Alloy thin plate. In the studied cooling temperate range, heat sources are due to Austenite to R phase transformation. Transformation temperatures, heat sources and energies are estimated from infrared temperature measurements and compared to differential scanning calorimetry results. The small 2 discrepancies are mainly explained by errors in DSC measurements due to thermal inertia and baseline determination

Anisotropy and crystal plasticity study of fcc polycrystalline Ni by nanoindentation

National audienceL'objectif de l'étude est de mettre en lumière l'anisotropie des matériaux cristallins de type cfc aux échelles micro et nanométriques. Des résultats numériques et expérimentaux de nanoindentation sont présentés. Les essais expérimentaux ont été réalisés sur un échantillon de nickel polycristallin, avec un indenteur de type Berkovich. Les simulations ont été menées sous le code éléments finis ZEBULON, en y intégrant un modèle de plasticité cristalline en grande déformation. Trois directions cristallographiques principales, correspondant à trois grains présentant ces mêmes directions , ont été choisies comme axe d'indentation, à savoir [001], [101] et [111]. Les empreintes ont été analysées au microscope à force atomique (AFM). La topographie de la surface autour des empreintes a révélé des lignes de glissement associées aux différents systèmes activés, ainsi que des remontées de matière (bourrelets) fortement anisotropes et non-symétriques, dépendantes de l'orientation du cristal par rapport à l'indenteur. Ces observations sont en accord avec les résultats des simulations numériques. L'effet de l'orientation de l'indenteur dans chacun des plans d'indentation a également été étudié expérimentalement et numériquement