Speaker: Paul Irofti (University of Bucharest). Machine learning helps us tackle large and apparently intractable optimization problems. Even though neural networks are by far the most popular choice in the field, we focus on dictionary learning (DL) for sparse representations (SR) instead. Our preference is motivated by the much simpler model that provides faster methods with a solid theoretical background, …

Speaker: Ciprian Păduraru Abstract: Even with access to the source code of a program, it is not easy to reverse engineer a program to find inputs for specific programs. This presentation starts with a practical walkthrough over classic methods for automating software testing, such as fuzz testing, symbolic and concolic execution. Then, a tool named …