We demonstrate that the Linear Multidimensional Assignment Problem with iid random costs is polynomially "-approximable almost surely (a. s.) via a simple greedy heuristic, f...
Abstract. We consider the minimization of a smooth convex function regularized by the mixture of prior models. This problem is generally difficult to solve even each simpler regula...
Junzhou Huang, Shaoting Zhang, Dimitris N. Metaxas
—Model-based test derivation for real-time system has been proven to be a hard problem for exhaustive test suites. Therefore, techniques for real-time testing do not aim to exhau...
We present several efficient dynamic data structures for point-enclosure queries, involving convex fat objects in R2 or R3. Our planar structures are actually fitted for a more ...
Alon Efrat, Matthew J. Katz, Frank Nielsen, Micha ...
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...