Stability of a learning algorithm with respect to small input perturbations is an important
property, as it implies that the derived models are robust with respect to the presence of …

Future 5G network ecosystems comprise a plethora of 3GPP and non 3GGP Radio Access
Technologies-RATs. Deployment scenarios envision a multi-layer use of macro, micro and …

We consider the problem of distributed K-clustering in a network of N agents where each
agent holds a part of a dataset. The goal for the agents is to agree, in a distributed manner …

Context: Data Mining (DM) method has been evolving year by year and as of today there is
also the enhancement of DM technique that can be run several times faster than the …

With the flood of information on the Web, it has become increasingly necessary for users to
utilize automated tools in order to find, extract, filter, and evaluate the desired information …

This thesis introduces new knowledge discovery algorithms based on fast data aggregation,
with a particular focus on coreset construction and data partitioning. A key idea pursued …

5G mobile communication systems will address unprecedented demands in terms of system
capacity, service latency and number of connected devices. Future 5G network ecosystems …

Context: Data Mining (DM) method has been evolving year by year and as of today there is
also the enhancement of DM technique that can be run several times faster than the …

A Complete Bibliography of ACM Transactions on Knowledge Discovery from Data (TKDD)
Page 1 A Complete Bibliography of ACM Transactions on Knowledge Discovery from Data (TKDD) …

In Data Mining an important research problem is the identification and analysis of theoretical
properties that characterize and explain the behavior of learning algorithms. Based on such …