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Sloan Working Papers

Research and Teaching Output of the MIT Community

Sloan Working Papers

 

Recent Submissions

  • The Big Data Newsvendor: Practical Insights from Machine Learning 
    Rudin, Cynthia; Vahn, Gah-Yi (DSpace, 2014-02-06)
    We investigate the newsvendor problem when one has n observations of p features related to the demand as well as past demands. Both small data (p=n = o(1)) and big data (p=n = O(1)) are considered. For both cases, we propose ...
  • An Interpretable Stroke Prediction Model using Rules and Bayesian Analysis 
    Letham, Benjamin; Rudin, Cynthia; McCormick, Tyler H.; Madigan, David (2013-11-15)
    We aim to produce predictive models that are not only accurate, but are also interpretable to human experts. Our models are decision lists, which consist of a series of if...then... statements (for example, if high blood ...
  • The Big Data Newsvendor: Practical Insights from Machine Learning Analysis 
    Rudin, Cynthia; Vahn, Gah-Yi (2013-10-16)
    We present a version of the newsvendor problem where one has n observations of p features as well as past demand. We consider both \big data" (p=n = O(1)) as well as small data (p=n = o(1)). For small data, we provide a ...
  • M.EOS: How General Management Matters 
    Santos, Jose (INSEAD Working Paper Series, 2013-07-09)
    This paper explores how general management matters and presents the foundation of a theory of general management as a theory of collective performance in the presence of the general manager. It proposes that general ...
  • Reactive Point Processes: A New Approach to Predicting Power Failures in Underground Electrical Systems 
    Ertekin, Seyda; Rudin, Cynthia; McCormick, Tyler H. (2013-09-26)
    Reactive point processes (RPP’s) are a new statistical model designed for predicting discrete events, incorporating self-exciting, self-regulating, and saturating components. The self-excitement occurs as a result of a ...
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