Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

The phenomenal success of our integrated circuits managed to obscure an awkward fact: they're not always the best way to solve problems. The features of modern computers—binary operations, separated ...

In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for static ...

Algorithms define the rules, conditions, and methodology that an AI will use when processing and analyzing data. Written by eWEEK content and product recommendations are editorially independent. We ...

Mathematics of Operations Research, Vol. 18, No. 1 (Feb., 1993), pp. 71-97 (27 pages) This paper is concerned with the design and probabilistic analysis of algorithms for the maximum-flow problem and ...

Part of understanding the meaning and power of algorithms means asking what new demands they might make of ethical frameworks, and how they might be held accountable to ethical standards. I develop a ...