This book addresses some theoretical aspects of semisupervised learning (SSL). The book
is organized as a collection of different contributions of authors who are experts on this topic …

In many application domains there is a large amount of unlabeled data but only a very
limited amount of labeled training data. One general approach that has been explored for …

This paper presents the results of a systematic review on the impacts of Software Process
Improvement (SPI) on developers. This review selected 26 studies from the highest quality …

Supervised learning—that is, learning from labeled examples—is an area of Machine
Learning that has reached substantial maturity. It has generated general-purpose and …

This paper focuses on joint cyber and physical attacks on power grids and presents methods
to retrieve the grid state information following such an attack. We consider a model where an …

Motivated by the recent cyber attack on the Ukrainian power grid, we study cyber attacks on
power grids that affect both the physical infrastructure and the data at the control center …

This paper focuses on cascading line failures in the transmission system of the power grid.
Recent large-scale power outages demonstrated the limitations of percolation-and epidemic …

Let G be an n-vertex graph that has a vertex separator of size k that partitions the graph into
connected components of size smaller than α n, for some fixed 2/3≤ α< 1. Such a separator …

The tasks of extracting (top-K) Frequent Itemsets (FIs) and Association Rules (ARs) are
fundamental primitives in data mining and database applications. Exact algorithms for these …

We propose a low-overhead scheme for detecting a network partition or cut in a sensor
network. Consider a network S of n sensors, modeled as points in a two-dimensional plane …