In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
We introduce a simple order-based greedy heuristic for learning discriminative structure within generative Bayesian network classifiers. We propose two methods for establishing an...
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
We study the problem of fast and energy-efficient data collection of sensory data using a mobile sink, in wireless sensor networks in which both the sensors and the sink move. Mot...
Constantinos Marios Angelopoulos, Sotiris E. Nikol...
In this paper, we propose a modification to the Boykov-Kolmogorov maximum flow algorithm [2] in order to make the algorithm preserve the topology of an initial interface. This alg...