Recent work has examined the estimation of models of stimulus-driven neural activity in which some linear filtering process is followed by a nonlinear, probabilistic spiking stag...
Jonathan Pillow, Liam Paninski, Eero P. Simoncelli
In this paper we analyze the problem of estimating a function from different noisy data sets collected by spatially distributed sensors and subject to unknown temporal shifts. We p...
We present a computational framework to automatically discover high-order temporal social patterns from very noisy and sparse location data. We introduce the concept of social foo...
In this paper, we present a novel method to adapt the temporal radio maps for indoor location determination by offsetting the variational environmental factors using data mining t...