One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
Lihong Li, Michael L. Littman, Christopher R. Mans...
We propose a sequential randomized algorithm, which at each step concentrates on functions having both low risk and low variance with respect to the previous step prediction functi...
Abstract— We consider the linear minimum meansquared error (LMMSE) estimation of a random vector of interest from its fusion frame measurements in presence noise and subspace era...
Ali Pezeshki, Gitta Kutyniok, A. Robert Calderbank
— Precoding is a well-known method to reach the promised performance and capacity of multiple-input multipleoutput (MIMO) systems. Recent investigations, when the transmitter has...
— This paper considers the quantization problem on the Grassmann manifold with dimension n and p. The unique contribution is the derivation of a closed-form formula for the volum...