Given a social network modeled as weighted graph GG, the influence maximization problem seeks kk vertices to become initially influenced, maximize expected number of influenced nodes under particular diffusion model. The has been proven be NP-hard, and most proposed solutions are approximate greedy algorithms, which can guarantee tunable approximation ratio for their results with respect optima...

This paper investigates the fundamental rate performances in highly promising cellular-enabled unmanned aerial vehicle (UAV) swarm networks, which can provide ubiquitous wireless connectivity for supporting various Internet of things (IoT) applications. We first formulations sum maximization and max-min rate, are two nonlinear optimization problems subject to constraints UAV transmit power ante...

The classical model for the analysis of progression of markers in HIV-infected patients is the mixed effects linear model. However, longitudinal studies of viral load are complicated by left censoring of the measures due to a lower quantification limit. We propose a full likelihood approach to estimate parameters from the linear mixed effects model for left-censored Gaussian data. For each subj...

Stochastic Gradient Descent has been widely studied with classification accuracy as a performance measure. However, these stochastic algorithms are not applicable when non-decomposable pairwise measures used, such Area under the ROC curve (AUC), standard metric used classes imbalanced. Several have proposed for optimizing AUC metric, one of recent being Proximal Algorithm (SPAM). downside gradi...

The 2D absolute phase estimation problem, in interferometric applications, is to infer absolute phase (not simply modulo-2π) from incomplete, noisy, and modulo-2π image observations. This is known to be a hard problem as the observation mechanism is nonlinear. In this paper we adopt the Bayesian approach. The observation density is 2π-periodic and accounts for the observation noise; the a prior...