Now showing items 1-4 of 4

    • Learning Outcome-Discriminative Dynamics in Multivariate Physiological Cohort Time Series 

      Nemati, Shamim; Lehman, Li-wei H.; Adams, Ryan Prescott (Institute of Electrical and Electronics Engineers, 2013)
      Model identification for physiological systems is complicated by changes between operating regimes and measurement artifacts. We present a solution to these problems by assuming that a cohort of physiological time series ...
    • Seed-Growth Heuristics for Graph Bisection 

      Ruml, Wheeler; Marks, Joe; Shieber, Stuart Merrill; Ngo, J. Thomas (1999)
      We investigate a family of algorithms for graph bisection that are based on a simple local connectivity heuristic, which we call seed-growth. We show how the heuristic can be combined with stochastic search procedures and ...
    • A Study of Heuristic Guesses for Adiabatic Quantum Computation 

      Perdomo-Ortiz, Alejandro; Venegas-Andraca, Salvador E.; Aspuru-Guzik, Alan (Springer Verlag, 2010)
      Adiabatic quantum computation (AQC) is a universal model for quantum computation which seeks to transform the initial ground state of a quantum system into a final ground state encoding the answer to a computational problem. ...
    • Two Foraging Algorithms for Robot Swarms Using Only Local Communication 

      Hoff, Nicholas R. III; Sagoff, Amelia; Wood, Robert J.; Nagpal, Radhika (IEEE, 2010)
      Large collections of robots have the potential to perform tasks collectively using distributed control algorithms. These algorithms require communication between robots to allow the robots to coordinate their behavior and ...