Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly applied to all queries, many studies have shown that different ranking functions favour different queries, and the retrieval performance can be significantly enhanced if an appropriate ranking function is selected for each indi...

Volcanic Risk Ranking (VRR) methods have been developed worldwide as a way to hierarchize the volcanic systems and help target strategies for risk reduction. Such hierarchization is especially important in areas characterized by large number of active volcanoes but limited resources. This case Latin America, where populations live nearby almost 300 volcanoes. Here we assess America with at leas...

Abstract To assess the operational safety risk of long-term evolution for metro (LTE-M) communication system more accurately, guide maintenance strategy, improved evidence theory and multi-attribute ideal reality comparative analysis (MAIRCA) approaches are proposed respectively. According to features LTE-M system, evaluation is established. The enhanced structural entropy weight method used co...

IET Cyber-Physical Systems: Theory & ApplicationsVolume 7, Issue 2 p. 112-112 CORRIGENDUMOpen Access Corrigendum: Cyber-physical component ranking for risk sensitivity analysis using betweenness centrality This article corrects the following: Amarachi Umunnakwe, Abhijeet Sahu, Mohammad Rasoul Narimani, Katherine Davis, Saman Zonouz, Volume 6Issue 3IET Applications pages: 139-150 First Published...

We formulate a local form of the bipartite ranking problem where the goal is to focus on the best instances. We propose a methodology based on the construction of real-valued scoring functions. We study empirical risk minimization of dedicated statistics which involve empirical quantiles of the scores. We first state the problem of finding the best instances which can be cast as a classificatio...

Counterparty risk denotes the risk that a party defaults in a bilateral contract. This risk not only depends on the two parties involved, but also on the risk from various other contracts each of these parties holds. In rather informal markets, such as the OTC (over-the-counter) derivative market, institutions only report their aggregated quarterly risk exposure, but no details about their coun...

Ranking is a central problem in information retrieval. Much work has been done in the recent years to automate the development of ranking models by means of supervised machine learning. Feature selection aims to provide sparse models which are computationally efficient to evaluate, and have good ranking performance. We propose integrating the feature selection as part of the training process fo...

Ranking is a central problem in information retrieval. Much work has been done in the recent years to automate the development of ranking models by means of supervised machine learning. Feature selection aims to provide sparse models which are computationally efficient to evaluate, and have good ranking performance. We propose integrating the feature selection as part of the training process fo...