In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
In this paper, we propose a new integration approach for simulation and behaviour in the learning context that is able to coherently manage the shared virtual environment for the ...
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...
Let r, B and w be positive integers. Let C be a linear code of length Bw and subspace of Fr 2. The k-regular-decoding problem is to find a nonzero codeword consisting of w length...
Abstract. We investigate the generalization behavior of sequential prediction (online) algorithms, when data are generated from a probability distribution. Using some newly develop...