Now showing items 21-25 of 25

  • Probabilistic Modeling of Sensor Artifacts in Critical Care 

    Manley, Geoffrey; Staudenmayer, Kristan; Cohen, Mitchell; Madden, Michael G.; Morabito, Diane; Aleks, Norm; Russell, Stuart (2008)
    We describe an application of probabilistic modeling and inference technology to the problem of analyzing sensor data in the setting of an intensive care unit (ICU). In particular, we consider the arterial-line blood ...
  • Qualitative and Quantitative Analysis of Chlorinated Solvents using Raman Spectroscopy and Machine Learning 

    Madden, Michael G.; Hennessey, Kenneth; Leger, Marc N.; Ryder, Alan G.; Conroy, Jennifer (2005)
    The unambiguous identification and quantification of hazardous materials is of increasing importance in many sectors such as waste disposal, pharmaceutical manufacturing, and environmental protection. One particular ...
  • Revealing the Origin and Nature of Drug Resistance of Dynamic Tumour Systems 

    Santiago-Mozos, Ricardo; Khan, Imtiaz A.; Madden, Michael G. (2010)
    In this paper, the authors identify the strategies that resistant subpopulations of cancer cells undertake to overcome the effect of the anticancer drug Topotecan. For the analyses of cell lineage data encoded from timelapse ...
  • A Survey of Recent Trends in One Class Classi cation 

    Khan, Shehroz S.; Madden, Michael G. (Springer Verlag - LNAI, 2009-08)
    The One Class Classification (OCC) problem is di fferent from the conventional binary/multi-class classi fication problem in the sense that in OCC, the negative class is either not present or not properly sampled. The ...
  • Towards inherently adaptive first person shooter agents using reinforcement learning 

    Glavin, Frank G. (2015-09-30)
    Reinforcement learning (RL) is a paradigm which involves an agent interacting with an environment. The agent carries out actions in the environment and receives positive reinforcement for actions that are deemed “good” and ...