A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
In this paper we present a novel expectation-maximization algorithm for inference of alternative splicing isoform frequencies from high-throughput transcriptome sequencing (RNA-Seq...
Marius Nicolae, Serghei Mangul, Ion I. Mandoiu, Al...
We consider the problem of determining the transmission power assignment that maximizes the lifetime of a data-gathering wireless sensor network with stationary nodes and static tr...
The Maximum Differential Backlog (MDB) control policy of Tassiulas and Ephremides has been shown to adaptively maximize the stable throughput of multihop wireless networks with ran...