On the robustness of the generalized fused lasso to prior specifications

Using networks as prior knowledge to guide model selection is a way to reach structured sparsity. In particular, the fused lasso that was originally designed to penalize differences of coefficients corresponding to successive features has been generalized to handle features whose effects are structured according to a given network. As any prior information, the network provided in the penalty may contain misleading edges that connect coefficients whose difference is not zero, and the extent to which the performance of the method depend on the suitability of the graph has never been clearly assessed. In this work we investigate the theoretical and empirical properties of the adaptive generalized fused lasso in the context of generalized linear models. In the fixed \(p\) setting, we show that, asymptotically, adding misleading edges in the graph does not prevent the adaptive generalized fused lasso from enjoying asymptotic oracle properties, while forgetting suitable edges can be more problematic. These theoretical results are complemented by an extensive simulation study that assesses the robustness of the adaptive generalized fused lasso against misspecification of the network as well as its applicability when theoretical coefficients are not exactly equal. Our contribution is also to evaluate the applicability of the generalized fused lasso for the joint modeling of multiple sparse regression functions. Illustrations are provided on two real data examples.     

Integrating Neural Networks and Semi-Markov Processes for Automated Knowledge Acquisition: An Application to Real-time Scheduling*

Recently, artificial neural networks (ANN) have gained attention as a promising modeling tool for building intelligent systems. A number of applications have been reported in areas varying from pattern recognition to bankruptcy prediction. In this paper, we present a creative methodology that integrates computer simulation, semi-Markov optimization, and ANN techniques for automated knowledge acquisition in real-time scheduling. The integrated approach focuses on the synergy between operations research and ANN in eliciting human knowledge, filtering inconsistent data, and building competent models capable of performing at the expert level. The new approach includes three main components. First, computer simulation is used to collect expert decisions. This step allows expert knowledge to be obtained in a non-intrusive way and minimizes the difficulties involved in interviewing experts, constructing repertory grids, or using other similar structures required for manual knowledge acquisition. The data collected from computer simulation are then optimized using a semi-Markov decision model to remove data redundancies, inconsistencies, and errors. Finally, the optimized data are used to build ANN-based expert systems. The integrated approach is evaluated by comparing it with the human expert and using ANN alone in the domain of real-time scheduling. The results indicate that ANN-based systems perform worse than human experts from whom the data were collected, but the integrated approach outperforms human experts and ANN models alone.     

Les relations entre droit international et droit européen du travail et leur incidence sur le développement du droit social international et européen

Des observations sur la manière dont le droit de l'Union européenne fait place aux instruments destinés à assurer la protection des travailleurs élaborés à l'échelle internationale ou à l'action des organisations internationales pour la protection des droits sociaux, cette contribution tire une typologie destinée à mettre au jour les liens, souvent tenus mais d'une grande diversité, qui rattachent le droit européen au «droit international du travail», au sens large.     

Producing ‘internal suspect bodies’: divisive effects of UK counter‐terrorism measures on Muslim communities in Leeds and Bradford

Research on UK government counter‐terrorism measures has claimed that Muslims are treated as a ‘suspect community’. However, there is limited research exploring the divisive effects that membership of a ‘suspect community’ has on relations within Muslim communities. Drawing from interviews with British Muslims living in Leeds or Bradford, I address this gap by explicating how co‐option of Muslim community members to counter extremism fractures relations within Muslim communities. I reveal how community members internalize fears of state targeting which precipitates internal disciplinary measures. I contribute the category of ‘internal suspect body’ which is materialized through two intersecting conditions within preventative counter‐terrorism: the suspected extremist for Muslims to look out for and suspected informer who might report fellow Muslims. I argue that the suspect community operates through a network of relations by which terrors of counter‐terrorism are reproduced within Muslim communities with divisive effects.     

Ground beetle (Coleoptera: Carabidae) communities on green roofs in Switzerland: synthesis and perspectives

Urban Ecosystems - Green roofs have recently gained recognition for their potential contribution to urban ecosystems by providing, among other services, habitat for plants and animals, and stepping...     

Engaging with Comparative Risk Appraisals: Public Views on Policy Priorities for Environmental Risk Governance

Communicating the rationale for allocating resources to manage policy priorities and their risks is challenging. Here, we demonstrate that environmental risks have diverse attributes and locales in their effects that may drive disproportionate responses among citizens. When 2,065 survey participants deployed summary information and their own understanding to assess 12 policy‐level environmental risks singularly, their assessment differed from a prior expert assessment. However, participants provided rankings similar to those of experts when these same 12 risks were considered as a group, allowing comparison between the different risks. Following this, when individuals were shown the prior expert assessment of this portfolio, they expressed a moderate level of confidence with the combined expert analysis. These are important findings for the comprehension of policy risks that may be subject to augmentation by climate change, their representation alongside other threats within national risk assessments, and interpretations of agency for public risk management by citizens and others.