NEWS

New paper in Applied Mathematics Letters

Andrei Pătraşcu and Paul Irofti published the paper On finite termination of an inexact Proximal Point algorithm in Applied Mathematics Letters.

New paper in Computational Optimization and Applications

Andrei Sipoş published the paper Abstract strongly convergent variants of the proximal point algorithm in Computational Optimization and Applications.

New talk in the Logic Seminar

Radu Iosif (CNRS - VERIMAG) will give on Tuesday, July 19, at 14:00 the talk On the Expressiveness of a Logic of Separated Relations in the Logic Seminar.



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


PhD Students


Research Assistants


Undergraduate and Master Students

Cristina Borza

MARIA-CRISTINA BORZA

ALEXANDRU MOCANU

Theodor Moroianu

THEODOR MOROIANU

Felix Puscasu

FELIX PUŞCAŞU

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




PROOF MINING SEMINAR

The seminar presents recent results on proof mining.




Past seminars

PUBLICATIONS