We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
We investigate the use of distributed measurements for estimating and updating the performance of a cellular system. Specifically, we discuss the number and placement of sensors in...
Liang Xiao, Larry J. Greenstein, Narayan B. Manday...
Many emerging distributed applications require the realtime processing of large amounts of data that are being updated continuously. Distributed stream processing systems offer a ...
We conduct laboratory experiments on variants of market scoring rule prediction markets, under different information distribution patterns, in order to evaluate the efficiency an...
Abstract— In this paper we present a dual-based decomposition method, called here the proximal center method, to solve distributed model predictive control (MPC) problems for cou...