We present a general method of designing fast approximation algorithms for cut-based minimization problems in undirected graphs. In particular, we develop a technique that given a...
A fast online algorithm was developed for polygonal approximation of signals and curves with a minimum number of line segments for a given constraint on the standard deviation of ...
We describe a simple random-sampling based procedure for producing sparse matrix approximations. Our procedure and analysis are extremely simple: the analysis uses nothing more th...
— This paper presents ALA (Adaptable Logarithm Approximation), a novel hardware architecture for the approximation of the base-2 logarithm of integers at an arbitrary accuracy, s...
Dimitris G. Bariamis, Dimitris Maroulis, Dimitrios...
Clustering is of central importance in a number of disciplines including Machine Learning, Statistics, and Data Mining. This paper has two foci: 1 It describes how existing algori...