We analyze the technique for reducing the complexity of entropy coding consisting in the a priori grouping of the source alphabet symbols, and in dividing the coding process in tw...
Abstract--We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclos...
Kenneth L. Clarkson, Elad Hazan, David P. Woodruff
— We investigate the use of Particle Swarm Optimization (PSO), and compare with Genetic Algorithms (GA), for a particular robot behavior-learning task: the training of an animat ...
Recently, there is a growing interest in working with tree-structured data in different applications and domains such as computational biology and natural language processing. Mor...
—We extend the existing network utility maximization (NUM) framework for wired networks to wireless sensor networks by formulating it in order to take into account interference a...
George Tichogiorgos, Kin K. Leung, Archan Misra, T...