BISIO , Federica

This paper moves from the affinities between two well-known learning schemes that apply randomization in the training process, namely, Extreme Learning Machines (ELMs) and the learning framework using similarity functions. These paradigms share a common approach involving data remapping and linear separators, but differ in the role of...

Every minute more than 320 new accounts are created on Twitter and more than 98,000 tweets are posted. Among the multitude of Twitter users, spammers and cybercriminals aim to pervade and strike legitimate users' accounts with a large amount of troublesome messages. Hence, the Social Network propagation opens new modalities for cyber-crime...

This research shows that inductive bias provides a valuable method to effectively tackle semi-supervised classification problems. In the learning theory framework, inductive bias provides a powerful tool, and allows one to shape the generalization properties of a learning machine. The paper formalizes semisupervised learning as a supervised...

This paper explores the theory of learning with similarity functions in the context of common-sense reasoning and natural language processing. Based on this theory, the proposed approach (called Sim-Predictor) is characterized by the process of remapping the input space into a new space which is able to convey the similarity between the input...

This research analyzes the affinities between two well-known learning schemes that apply randomization in the training process, namely, Extreme Learning Machines (ELMs) and the learning framework using similarity functions. These paradigms share a common approach to inductive learning, which combines an explicit data remapping with a linear...

In the Internet age, malicious software (malware) represents a serious threat to the security of information systems. Malware-detection systems to protect computers must perform a real-time analysis of the executable files. The paper shows that machine-learning methods can support the challenging, yet critical, task of unseen malware...

Sentiment analysis research has acquired a growing importance due to its applications in several different fields. A large number of companies have included the analysis of opinions and sentiments of costumers as a part of their mission. Therefore, the analysis and automatic classification of large corpora of documents in natural language,...