We present a method for hierarchical data approximation using curved quadratic simplicial elements for domain decomposition. Scientific data defined over two- or three-dimensional ...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Given a collection Ᏺ of subsets of S ϭ {1, . . . , n}, set cover is the problem of selecting as few as possible subsets from Ᏺ such that their union covers S, and max k-cover ...
—We study the problem of approximating a 3D solid with a union of overlapping spheres. In comparison with a stateof-the-art approach, our method offers more than an order of magn...
We present an on-line Dynamic Voltage Scaling (DVS) algorithm for preemptive fixed-priority real-time systems called low power Limited Demand Analysis with Transition overhead (l...