—We consider approaches for similarity search in correlated, high-dimensional data-sets, which are derived within a clustering framework. We note that indexing by “vector appro...
Dimensionality reduction is the process by which a set of data points in a higher dimensional space are mapped to a lower dimension while maintaining certain properties of these p...
Improving logic capacity by time-sharing, dynamically reconfigurable FPGAs are employed to handle designs of high complexity and functionality. In this paper, we model each task ...
In this paper techniques from multidimensional scaling and graph drawing are coupled to provide an overview-and-detail style method for visualising a high dimensional dataset whos...
We consider the problem of approximating a set P of n points in Rd by a j-dimensional subspace under the p measure, in which we wish to minimize the sum of p distances from each p...
Dan Feldman, Morteza Monemizadeh, Christian Sohler...