The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Temporal difference (TD) algorithms are attractive for reinforcement learning due to their ease-of-implementation and use of "bootstrapped" return estimates to make effi...
We present a description of two small audio/visual immersive installations. The main framework is an interactive structure that enables multiple participants to generate jazz impr...
Constance G. Baltera, Sara B. Smith, Judy A. Frank...
Although Bayesian model averaging is theoretically the optimal method for combining learned models, it has seen very little use in machine learning. In this paper we study its app...