Samuel P. Midkiff, Jose E. Moreira, Manish Gupta, Siddhartha Chatterjee, Jeanne Ferrante, Jan Prins, William Pugh, Chau-
This volume contains the papers presented at the 13th International Workshop on Languages and Compilers for Parallel Computing. It also contains extended abstracts of submissions that were accepted as posters. The workshop was held at the IBM T. J. Watson Research Center in Yorktown Heights, New York. As in previous years, the workshop focused on issues in optimizing compilers, languages, and software environments for high performance computing. This continues a trend in which languages, compilers, and software environments for high performance computing, and not strictly parallel computing,...
This volume contains the papers presented at the 13th International Workshop on Languages and Compilers for Parallel Computing. It also contains exten...
Digital identity and access management (DIAM) systems are essential to security frameworks for their ability to rapidly and consistently confirm identities and to control individuals' access to resources and services. However, administering digital identities and system access rights can be challenging even under stable conditions. Digital Identity and Access Management: Technologies and Frameworks explores important and emerging advancements in DIAM systems. The book helps researchers and practitioners in digital identity management to generate innovative answers to an assortment of...
Digital identity and access management (DIAM) systems are essential to security frameworks for their ability to rapidly and consistently confirm ident...
Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time series-based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types including high-dimensional data, uncertain data, stream data, network data, time series data, spatial data, and spatio-temporal data. While there have been many tutorials and...
Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data m...