Search Results (4)
Representing and exploiting benchmarking data for optimisation and learning
The rapid advancements in Machine Learning (ML) and Black-Box Optimization (BBO) have led to an increased reliance on benchmarking data for evaluating and comparing algorithms across diverse domain tasks. However, the effective exploitation of this data is hindered by challenges such as syntactic variability, semantic ambiguity, and lack of standardization. …
Machine learning methodology for automatic metadata assignment in cultural heritage archives
This thesis introduces a novel machine learning methodology for automatically assigning metadata to digitized artifacts in cultural heritage. Cultural heritage is an example of a domain that requires expert labeling, with few pre-existing labeled datasets and where simply getting more labeled data is challenging. The societal importance of cultural heritage …
Information spreading barriers in news
News spreads in many patterns, structures, and dynamics that change throughout time. For a variety of reasons, certain news is only covered in a particular area. Language, economy, geography, politics, time zone, and culture are just a few of the many barriers that prevent news from reaching a larger audience. …
An automated vulnerability detection for website security
Although large research efforts on web application security have been invested for more than a decade, the security of web applications is still a challenging problem. The main focus of the cybersecurity community has been to make operating systems and communication networks more secure and harder for attackers to penetrate. …