We give near-optimal sketching and streaming algorithms for estimating Shannon entropy in the most general streaming model, with arbitrary insertions and deletions. This improves ...
Nicholas J. A. Harvey, Jelani Nelson, Krzysztof On...
We briefly present and analyze, from a geometric viewpoint, strategies for designing algorithms to factor bivariate approximate polynomials in [x, y]. Given a composite polyno...
In this research, we propose to use the discrete cosine transform to approximate the cumulative distributions of data cube cells' values. The cosine transform is known to have...
In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
We propose a new approach to value-directed belief state approximationfor POMDPs. The valuedirected model allows one to choose approximation methods for belief state monitoringtha...