Abstract.Many different evaluation measures for dimensionality reduction can be summarized based on the co-ranking framework [6]. Here, we extend this framework in two ways: (i) we show that the current parameterization of the quality shows unpredictable behavior, even in simple settings, and we propose a different parameterization which yields more intuitive results; (ii) we propose how to link the quality to point-wise quality measures which can directly be integrated into the visualization.

In the wake of the pandemic of coronavirus disease 2019 , contact tracing has become a key element of strategies to control the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Given the rapid and intense spread of SARS-CoV-2, digital contact tracing has emerged as a potential complementary tool to support containment and mitigation efforts. Early modelling studies highlighted the potential of digital contact tracing to break transmission chains, and Google and Apple subsequently developed the Exposure Notification (EN) framework, making it available to the vast majority of smartphones. A growing number of governments have launched or announced EN-based contact tracing apps, but their effectiveness remains unknown. Here, we report early findings of the digital contact tracing app deployment in Switzerland. We demonstrate proof-of-principle that digital contact tracing reaches exposed contacts, who then test positive for SARS-CoV-2. This indicates that digital contact tracing is an effective complementary tool for controlling the spread of SARS-CoV-2. Continued technical improvement and international compatibility can further increase the efficacy, particularly also across country borders.

No abstract

Abstract. Private information retrieval (PIR) allows clients to retrieve records from online database servers without revealing to the servers any information about what records are being retrieved. To achieve this, the servers must typically do a computation involving the entire database for each query. Previous work by Ishai et al. has suggested using batch codes to allow a single client (or collaborating clients) to retrieve multiple records simultaneously while allowing the server computation to scale sublinearly with the number of records fetched. In this work, we observe a useful mathematical relationship between batch codes and efficient matrix multiplication algorithms, and use this to design a PIR server algorithm that achieves sublinear scaling in the number of records fetched, even when they are being requested by distinct, non-collaborating clients; indeed, the clients can be completely unaware that the servers are implementing our optimization. Our server algorithm is several times faster, when enough records are fetched, than existing optimized PIR severs. As an application of our work, we show how retrieving proofs of inclusion of certificates in a Certificate Transparency log server can be made privacy friendly using multi-client PIR.