The main aim of this paper is to extend the single-agent policy gradient method for multiagent domains where all agents share the same utility function. We formulate these team pro...
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
This paper proposes the fractional component analysis (FCA), whose goal is to decompose the observed signal into component signals and recover their fractions. The uniqueness of o...
The goal of this work is to study the asymptotic and finite sample properties of an estimator of a nonlinear regression function when errors are spatially correlated, and when the...
— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...