Seminar Details:

LANS Informal Seminar
"Polynomial Interpolation for Predicting Decisions and Recovering Missing Data"

DATE: April 15, 2009

TIME: 15:00:00 - 16:00:00
SPEAKER: Oleg Roderick and Ilya Safro, MCS
LOCATION: Building 221 Conference Room A261, Argonne National Laboratory

In this work we improve the existing tools for the recovery and prediction of human decisions based on multiple factors. We use essentially a latent factor method, and obtain the decision-influencing factors from the observed correlations in the available statistical information by singular value decomposition-based principal factor identification. We generalize on widely-used linear representations of decision-making functions by using adaptive high-order polynomial interpolation and applying an iterative and adaptive post-processing to arrive at an estimated probability of every possible outcome of a decision. The novelty of the method consists in the use of flexible, nonlinear predictive functions, and in the suggested post-processing procedure. Our experiments show that the introduced approach is at least competitive in the class of SVD-based prediction methods, and that the precision grows with the increase in the order of the polynomial basis. We suggest that the method may be successfully applied instead of a widely used linear SVD-based methods.


Please send questions or suggestions to Charlotte Haley: haley at anl dot gov.