Now showing items 1-3 of 3

    • Adaptive ensemble learning with confidence bounds 

      Tekin, C.; Yoon, J.; Schaar, M. V. D. (Institute of Electrical and Electronics Engineers Inc., 2017)
      Extracting actionable intelligence from distributed, heterogeneous, correlated, and high-dimensional data sources requires run-time processing and learning both locally and globally. In the last decade, a large number of ...
    • Adaptive ensemble learning with confidence bounds for personalized diagnosis 

      Tekin, Cem; Yoon, J.; Van Der Schaar, M. (AAAI Press, 2016)
      With the advances in the field of medical informatics, automated clinical decision support systems are becoming the de facto standard in personalized diagnosis. In order to establish high accuracy and confidence in ...
    • Two learning approaches for protein name extraction 

      Tatar, S.; Cicekli, I. (Academic Press, 2009)
      Protein name extraction, one of the basic tasks in automatic extraction of information from biological texts, remains challenging. In this paper, we explore the use of two different machine learning techniques and present ...