Bayes statistics and statistical physics have the common mathematical structure, where the log likelihood function corresponds to the random Hamiltonian. Recently, it was discovere...
A Bayesian approach to analyze the modes of variation in a set of curves is suggested. It is based on a generative model thus allowing for noisy and sparse observations of curves....
We describe the design and experimental validation of a large heterogeneous mobile robot team built for the DARPA Software for Distributed Robotics (SDR) program. The core challen...
Andrew Howard, Lynne E. Parker, Gaurav S. Sukhatme
Random forests were introduced as a machine learning tool in Breiman (2001) and have since proven to be very popular and powerful for high-dimensional regression and classificatio...
Abstract--This paper offers a new technique for spatially adaptive estimation. The local likelihood is exploited for nonparametric modeling of observations and estimated signals. T...