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We present a novel per-dimension learning rate method for gradient descent called ADADELTA. The method dynamically adapts over… Expand We present Resilient Distributed Datasets (RDDs), a distributed memory abstraction that lets programmers perform in-memory… Expand Cluster computing applications like MapReduce and Dryad transfer massive amounts of data between their computation stages. These… Expand MapReduce and its variants have been highly successful in implementing large-scale data-intensive applications on commodity… Expand Clustering is the division of data into groups of similar objects. In clustering, some details are disregarded in exchange for… Expand Cities and regions have long captured the imagination of sociologists, economists, and urbanists. From Alfred Marshall to Robert… Expand Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by… Expand Sensor webs consisting of nodes with limited battery power and wireless communications are deployed to collect useful information… Expand Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large… Expand Abstract This paper transmits a FORTRAN-IV coding of the fuzzy c -means (FCM) clustering program. The FCM program is applicable… Expand