The training of Emergent Self-organizing Maps (ESOM ) with large datasets can be a computationally demanding task. Batch learning may be used to speed up training. It is demonstrat...
We propose Link Propagation as a new semi-supervised learning method for link prediction problems, where the task is to predict unknown parts of the network structure by using aux...
Compressive sensing is the reconstruction of sparse images or signals from very few samples, by means of solving a tractable optimization problem. In the context of MRI, this can ...
This paper presents Frame Based Fair Multiprocessor Scheduler (FBFMS) which provides accurate real-time proportional fair scheduling for a set of dynamic tasks on a symmetric mult...
Finding the minimum column multiplicity for a bound set of variables is an important problem in Curtis decomposition. To investigate this problem, we compared two graphcoloring pr...
Marek A. Perkowski, Rahul Malvi, Stan Grygiel, Mic...