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June 11, 2026
Doctoral Student at HSE University Reveals Hidden Layout of Ancient Parion
İdil Malgil, a researcher at HSE University, conducted a UAV-based LiDAR survey of the ancient Roman city of Parion in present-day Turkey. The high density of the scans allowed the team to detect subtle terrain features concealed beneath the ground and vegetation. The survey revealed traces of entire neighbourhoods, terraced structures, and walls that had remained invisible during routine excavations and could not be identified through aerial photography. The findings have been published in Ancient Civilizations from Scythia to Siberia.
June 11, 2026
Mathematicians from Nizhny Novgorod and Shanghai Study System Stability
Mathematicians at HSE University–Nizhny Novgorod, in collaboration with colleagues from Tongji University in Shanghai, are investigating the fundamental causes of structural stability in systems and the mechanisms underlying its disruption. In this interview with the HSE News Service, Prof. Olga Pochinka, Head of the International Laboratory of Dynamical Systems and Applications at HSE University–Nizhny Novgorod and leader of the project ‘Qualitative Theory of Systems of Ordinary and Partial Differential Equations,’ discusses the project, which is being implemented as part of HSE University's International Academic Cooperation programme.
June 11, 2026
Neurolinguists Assist in Awake Surgery on 11-Year-Old Patient with Epilepsy
Researchers at the HSE Centre for Language and Brain took part in a rare awake neurosurgical procedure performed on an 11-year-old patient with drug-resistant epilepsy. Working alongside surgeons at the Voyno-Yasenetsky Centre of Specialised Medical Care for Children in Solntsevo, they monitored the resection of a portion of the left temporal lobe, where the epileptic focus had been identified.

 

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Mathematical Optimization Theory and Operations Research. 23rd International Conference, MOTOR 2024, Omsk, Russia, June 30–July 6, 2024, Proceedings. LNCS, volume 14766

Springer, 2024.
Under the general editorship: A. Eremeev, Michael Khachay, Y. Kochetov, V. Mazalov, Pardalos P. M.

This volume contains the refereed proceedings of the 23rd International Conference on Mathematical Optimization Theory and Operations Research (MOTOR 2024)1 held from June 30 to July 06, 2024, in Omsk, Russia. The MOTOR conference joined several well-known conferences on mathematical programming, optimization, and operations research which had been held in the Urals, Siberia and the Russian Far East for a number of decades. Previous editions of MOTOR were held in Yekaterinburg, Novosibirsk, Irkutsk and Petrozavodsk.

 

 

Chapters
Robustness of Graphical Lasso Optimization Algorithm for Learning a Graphical Model
Valeriy Kalyagin, Ilya Kostylev, , in: Mathematical Optimization Theory and Operations Research. 23rd International Conference, MOTOR 2024, Omsk, Russia, June 30–July 6, 2024, Proceedings. LNCS, volume 14766.: Springer, 2024. P. 337–348.
Problem of learning a graphical model (graphical model selection problem) consists of recovering a conditional dependence structure (concentration graph) from data given as a sample of observations from a random vector. Various algorithms to solve this problem are known. One class of algorithms is related with convex optimization problem with additional lasso regularization term. Such ...
Added: August 9, 2024
Research target: Computer Science
Language: English
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DOI
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Keywords: operations researchMathematical Optimization Theory
Mathematical Optimization Theory and Operations Research. 23rd International Conference, MOTOR 2024, Omsk, Russia, June 30–July 6, 2024, Proceedings. LNCS, volume 14766
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