It is crucial to study basic principles that support adaptive and scalable retrieval functions in large networked environments such as the Web, where information is distributed am...
Large, dynamic, and ad-hoc organizations must frequently initiate data integration and sharing efforts with insufficient awareness of how organizational data sources are related. ...
Ken Smith, Craig Bonaceto, Chris Wolf, Beth Yost, ...
A linear multivariate measurement error model AX = B is considered. The errors in A B are row-wise finite dependent, and within each row, the errors may be correlated. Some of th...
Alexander Kukush, Ivan Markovsky, Sabine Van Huffe...
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Convergent scheduling is a general framework for instruction scheduling and cluster assignment for parallel, clustered architectures. A convergent scheduler is composed of many ind...
Walter Lee, Diego Puppin, Shane Swenson, Saman P. ...