NEWS

New talk in the LOS Seminar


Andra Băltoiu will give on Thursday, October 19, 2021 at 14:00 the talk Dictionary Learning Heuristics Control Through Adaptive Strategies and Applications to Anomaly Detection in the LOS seminar.

New paper in Optimization Letters

Andrei Sipoş published the paper Quantitative inconsistent feasibility for averaged mappings in Optimization Letters.


New paper in IEEE Transactions on Signal Processing

Cristian Rusu and Lorenzo Rosasco published the paper Constructing fast approximate eigenspaces with application to the fast graph Fourier transforms in IEEE Transactions on Signal Processing.



More news...

ABOUT

The Research Center for Logic, Optimization and Security (LOS) was founded in October 2020 by Laurenţiu Leuştean (head), Paul Irofti and Andrei Pătraşcu.
Our main objective is to stimulate interdisciplinary research in the fields of logic, optimization and security. We are interested both in fundamental research as well as in industrial applications. We focus on proof mining and applications to optimization, ergodic theory and nonlinear analysis, convex optimization for machine learning, signal processing and matrix factorization (dictionary learning), security, anomaly detection and anti-money laundry.

Contact
Hall 317, Faculty of Mathematics and Computer Science,
Academiei 14, 010014 Bucharest, Romania
Email: los@fmi.unibuc.ro

PEOPLE

Faculty


Associated researchers


Students

Ruxandra Balucea

RUXANDRA BĂLUCEA

HORAŢIU CHEVAL

Bogdan Macovei

BOGDAN MACOVEI

PROJECTS

NetAlert (SOL4/2021)

NetAlert aims to create a hardware-software sensor solution for detecting anomalies in computer networks based on the monitoring and analysis of data packets. The network-mounted sensor will provide real-time alerts on abnormal traffic behaviors using two complementary approaches:
(i) static analysis based on rules and behavioral patterns;
(ii) machine learning (ML) analysis without prior expert knowledge.

DDNET (12PD/2020)

The main goal of this project, called DDNET, is to adapt and propose new dictionary learning methods for solving untractable fault detection and isolation problems found in distribution networks. Given a large dataset of sensor measurements from the distribution network, the dictionary learning algorithms should be able to produce the subset of network nodes where faults exist.


Graphomaly (287PED/2020)

The proposed project, called Graphomaly, aims to create a Python software package for anomaly detection in graphs that model financial transactions, with the purpose of discovering fraudulent behavior like money laundering, illegal networks, tax evasion, scams, etc. Such a toolbox is necessary in banks, where fraud detection departments still use mostly human experts.




StOpAnomaly (143PD/2020)

StOpAnomaly aims to create, analyze and implement numerical optimization algorithms for large-scale optimization focusing on robust anomaly detection models based on decomposition and one-class classification. The research will be directed towards development of a toolbox containing scalable stochastic algorithms that can be used to detect several classes of anomalies in noisy large datasets.

SEMINARS

Scientific seminars organized by LOS members

LOS SEMINAR

The working seminar of the LOS research center.

LOGIC SEMINAR

The logic seminar features talks on mathematical logic, philosophical logic and logical aspects of computer science.




SECURITY SEMINAR

The Cyber-security seminar brings together academic and industry folk to discuss hot topics in the field ranging from operating systems, static and dynamic analysis of executables to fraud detection and security centric machine learning techniques.




LEAN SEMINAR

The Lean seminar is addressed to students who wish to master the Lean functional programming language.


PUBLICATIONS