High-Speed Function Approximation

We address a new learning problem where the goal is to build a predictive model that minimizes prediction time (the time taken to make a prediction) subject to a constraint on model accuracy. Our solution is a generic framework that leverages existing data mining algorithms without requiring any modifications to these algorithms. We show a first application of our framework to a combustion simulation problem. Our experimental evaluation shows significant improvements over existing methods; prediction time typically is improved by a factor between 2 and 6.

• Type: Conference
• Year: 2007
• Where: ICDM
• Authors: Biswanath Panda, Mirek Riedewald, Johannes Gehrke, Stephen B. Pope
• Keywords: Combustion Simulation Problem, Data Mining, Data Mining Algorithms, ICDM 2007, Prediction Time