Machine Learning Framework for Security Applications

Facultatea de Matematica si Informatica, sala 202

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,

Classical and quantum degrees of truth: a new look at the effects of a Hilbert space

Facultatea de Matematica si Informatica, sala 202

Speaker: Roberto Giuntini (University of Cagliari). We investigate certain Brouwer-Zadeh lattices that serve as abstract counterparts of lattices of effects in Hilbert spaces under the spectral ordering. These algebras, called PBZ∗-lattices, can also be seen as generalisations of orthomodular lattices and are remarkable for the collapse of three notions of “sharpness” that are distinct in general

Logical Foundations: Total and Partial Maps

Facultatea de Matematica si Informatica, sala 202

Speaker: Miriam Costan. This week we continue exploring Coq based on the Logical Foundations volume of Software Foundations, chapter "Total and Partial Maps"

How to find bugs in your (x86) code; RIVER tool – current state and future

Facultatea de Matematica si Informatica, sala 202

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

Logical Foundations: Simple Imperative Programs

Facultatea de Matematica si Informatica, sala 202

Presenter: Traian Serbanuta. This week we continue exploring Coq based on the Logical Foundations volume of Software Foundations, chapter "IMP: Simple Imperative Programs"

The finitary content of sunny nonexpansive retractions

Facultatea de Matematica si Informatica, sala 202

Andrei Sipoș (TU Darmstadt & IMAR). The goal of proof mining is to extract quantitative information out of proofs in mainstream mathematics which are not necessarily fully constructive. Often, such proofs make use of strong mathematical principles, but a preliminary analysis may show that they are not actually needed, so the proof may be carried