Machine Learning

Machine learning for high-dimensional dynamic stochastic economies

We present a novel computational framework that can compute global solutions to high-dimensional dynamic stochastic economic models on irregular state space geometries. This framework can also resolve value and policy functions’ local features and …

Inferring personalized visual satisfaction profiles in daylit offices from comparative preferences using a Bayesian approach

This paper presents a new method for developing personalized visual satisfaction profiles in private daylit offices using Bayesian inference. Unlike previous studies based on action data, a set of experiments with human subjects and changing visual …