https://uniba.sk/ Najnovšie novinky sk https://uniba.sk/fileadmin/tt_news_article.gif https://uniba.sk/ Najnovšie novinky TYPO3 - get.content.right http://blogs.law.harvard.edu/tech/rss Thu, 31 Dec 2026 00:00:00 +0100 https://uniba.sk/ March 6, 2025, Prague FLAMMA award, which recognises inspiring female lawyers in the Czech and Slovak Republics. The award ceremony took place in Prague as part of the #PRVNÍCH100LET project and was held for the fourth time. Among the honoured female lawyers were also prominent personalities from the legal world, including Oxford professor Barbora Havelková, future Chief Public Prosecutor Lenka Bradáčová, and Slovak anti-discrimination law expert Janka Debrecéniová. The laureates were selected by a jury consisting of more than fifty ambassadors of the project. Among them were prominent personalities of the legal community, such as judge of the European Court of Human Rights Katarína Šimáčková, Vice President of the Supreme Court of the Slovak Republic Andrea Moravčíková, and former Czech EU Commissioner Věra Jourová. The FLAMMA award highlights exceptional female lawyers who contribute to the development of the legal environment and inspire future generations through their work, expertise and dedication. Congratulations to Mária Havelková on this significant achievement! ]]> [PraF] EN Titulka - úzke novinky [PraF] Titulka - úzke novinky - z uniba.sk Thu, 06 Mar 2025 10:37:00 +0100 https://uniba.sk/ Monday 10.3.2025 at 13:10, Lecture room I/9 Pavol Kollár:
Counting an Unreasonable Amount of Objects in a Reasonable Amount of Time Abstract:
Considering all possible cases is good when you can write them down and consider them one-by-one. Things get much more complicated, however, when the number of cases grows so big, not even a computer could tractably consider all them.
Such is the case with our line of research, where we use advanced algebraic and computational methods to solve combinatorial problems. Our topic of study today features graphs with high symmetry levels, which have a hierarchy in them based on “how close to being a Cayley graph” they are. The deciding criterion turns out to be an interesting object of study in its own right, generalising transitivity of group actions.
In the talk we build upon our previous work of using generating polynomials, which is a general purpose algorithm, to get upper bounds on the number of r-regular families. Once this algorithm is in place, we need to understand what makes inputs bad and good, so that we can pick our algorithm’s inputs in a smart and useful way. Last, but not least, we present a probabilistic extension of a brute-force algorithm that lets us approximately count the number of solutions to a problem that would otherwise be untractable. More information ]]> [FMFI] Prednášky a semináre [FMFI] Kalendár Pavol.Kollar@fmph.uniba.sk Thu, 06 Mar 2025 10:21:00 +0100 https://uniba.sk/ 5 March 2025, Faculty of Law, Comenius University in Bratislava [PraF] Titulka - úzke novinky - z uniba.sk [PraF] EN Titulka - úzke novinky Thu, 06 Mar 2025 10:22:00 +0100 https://uniba.sk/ 4 March 2025, Mochovce Law Students on Site Trips concept in complementing legal education in practice. ]]> [PraF] Titulka - úzke novinky - z uniba.sk [PraF] EN Titulka - úzke novinky Thu, 06 Mar 2025 10:05:00 +0100 https://uniba.sk/ Friday 14.3.2025 at 13:30, Lecture room C Arkady Leiderman (Ben-Gurion University of the Negev):
Kolmogorov Superposition Theorem and its applications in Topological Algebra Abstract]]> [FMFI] Prednášky a semináre [FMFI] Kalendár Tibor.Macko@fmph.uniba.sk Wed, 05 Mar 2025 09:38:00 +0100 https://uniba.sk/ Friday 7.3.2025 at 13:15 hod., Lecture room M IX (online too) Róbert Jajcay:
Graphs of Large Girth - A Survey by Christian Reiher
Abstract:
A recent survey of Christian Reiher covers in large parts the same topics as those covered by the dynamic survey on cages. Nevertheless, the result is quite different and constitutes a very interesting complement to the cage survey. The aim of the talk is to visit those parts of Reiher's survey not covered in the other survey, draw the connections between the two, and discuss the proofs emphasizing the overlap between the Algebraic and Extremal Graph Theories. The Cage Survey can be found at https://www.combinatorics.org/ojs/index.php/eljc/article/view/DS16
The Girth Survey is posted at https://arxiv.org/abs/2403.13571
  Those of you who are not able to attend in person or who are still uncertain about the safety of attending in person are welcome to attend via MS Teams. In either case, we hope to see as many of you as possible (either in person or virtually) at our Friday gatherings. ]]> [FMFI] Prednášky a semináre [FMFI] Kalendár Martin.Macaj@fmph.uniba.sk Wed, 05 Mar 2025 08:56:00 +0100 https://uniba.sk/ March 6th - May 22nd, 2025 When?  March 6th - May 22nd, 2025
Every THURSDAY from 15:15 until 16:35            
Where? In the Gym of the Faculty of Law, Comenius University, Šafárikovo nám. 6 , - (minus) 1st floor Maximum:  20 students
Duration: 80 minutes
Language: English
Cost: Free of charge MANDATORY REGISTRATION:
https://outlook.office365.com/book/HolisticStudentYogawithAmit@live.uniba.sk/  INFORMATION AND REGISTRATION FOR BOTH INTERNATIONAL AND SLOVAK STUDENTS HERE: https://uniba.sk/index.php?id=27957]]> [LF] Titulka - široké novinky Mon, 03 Mar 2025 15:27:00 +0100 https://uniba.sk/ Friday 7.3.2025 at 11:00, Lecture room C Martin Takáč (Zayed University of Artificial Intelligence):
Solving Combinatorial Problems Using Reinforcement Learning and Large Language Models
Abstract: 
The Vehicle Routing Problem (VRP) remains a critical challenge in logistics and resource management due to its NP-hard nature and the complexity of stochastic demands. This talk explores solutions to VRP through the application of Reinforcement Learning (RL) and Large Language Models (LLMs). Firstly, we introduce a novel end-to-end framework for solving the Vehicle Routing Problem using RL. Our approach leverages the correlation between stochastic demands and other observable variables, demonstrating that non-i.i.d. stochastic demands can enhance routing solutions. In parallel, we discuss the application of Large Language Models (LLMs) to VRP through a novel prompting strategy called Self-Guiding Exploration (SGE). This method enhances LLMs’ ability to solve combinatorial problems by autonomously generating multiple thought trajectories for each VRP task. These trajectories are decomposed into actionable subtasks, executed sequentially, and refined to ensure optimal outcomes. Our findings indicate that SGE significantly outperforms existing prompting strategies, demonstrating its effectiveness in optimizing VRP solutions. Martin Takac is an Associate Professor and the Deputy Department Chair of Machine Learning at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in the UAE. Prior to joining MBZUAI, he was an Associate Professor in the Department of Industrial and Systems Engineering at Lehigh University, where he had been on faculty since 2014. He earned his B.S. (2008) and M.S. (2010) degrees in Mathematics from Comenius University, Slovakia, and his Ph.D. (2014) in Mathematics from the University of Edinburgh, United Kingdom. Martin’s research focuses on the development and analysis of algorithms for machine learning, AI-driven scientific discovery, protein-DNA interaction studies, and the application of machine learning to energy systems. His work has earned him several prestigious awards, including the Best Ph.D. Dissertation Award by the OR Society (2014), the Leslie Fox Prize (2nd Prize; 2013) by the Institute for Mathematics and its Applications, the INFORMS Computing Society Best Student Paper Award (runner-up; 2012), and the Charles Broyden Prize for the best paper published in the 2022 volume of Optimization Methods and Software. He has received funding from multiple U.S. National Science Foundation programs, including a TRIPODS Institute grant in collaboration with Lehigh, Northwestern, and Boston University. Recently, he was also awarded three grants in partnership with the Weizmann Institute of Science. Martin has served as an Associate Editor for journals such as Mathematical Programming Computation, Journal of Optimization Theory and Applications, and Optimization Methods and Software. Additionally, he has taken on the role of Area Chair for top conferences such as AISTATS, NeurIPS, and ICLR, and served as a Senior Area Chair for NeurIPS 2024. ]]> [FMFI] Prednášky a semináre [FMFI] Kalendár Tomas.Vinar@fmph.uniba.sk Sun, 02 Mar 2025 15:22:00 +0100 https://uniba.sk/ Tuesday 11.3.2025 at 14:00, Lecture room F2/125 Dr. Ján Pulmann (University of Edinburgh):
Lagrangian Relations, Half-Densities and Quantum L_∞ Algebras
Abstrakt:
Lagrangian relations model maps and more general correspondences between physical systems. In Batalin-Vilkovisky formalism, it is natural to generalize Lagrangian relations to distributional half-densities, as advocated by Ševera. We give a rigorous definition of linear distributional half-densities and describe their composition, thus constructing a linear version of a quantum odd symplectic category. As an application, we describe the computation of the BV effective action as a composition in this category. Based on [arXiv:2401.06110], joint with B. Jurčo and M. Zika. ]]> [FMFI] Prednášky a semináre [FMFI] Kalendár Peter.Matak@fmph.uniba.sk Thu, 27 Feb 2025 22:51:00 +0100 https://uniba.sk/ 27 February 2025, Košice, Bratislava Universities Join Forces with the Commercial Sector: Machine Learning to Streamline Legal Text Analysis Pavol Jozef Šafárik University in Košice (UPJŠ), Comenius University in Bratislava, Faculty of Law (PraF UK), and Wolters Kluwer SR s.r.o. (WK) are jointly implementing a project titled "Automation of Legal Text Analysis Based on Machine Learning" (ALTAML). The project is supported by the Slovakia National Recovery and Resilience Plan. The aim of the project is to utilize machine learning methods for more efficient processing and analysis of legal texts. This technology has the potential to better identify relationships between legal texts, detect deviations from established practices, and streamline access to legal information. The main benefits of the project include the automation of the legal text processing, which will speed up and streamline the work with legal documents. The application of machine learning and data analysis methods will enable a deeper understanding and more efficient use of legal information. These methods will facilitate navigation through complex legal texts as well as allow the identification of relationships between them, which is crucial for understanding broader contexts within the legal system. Detection of deviations from established decision-making practices is another essential benefit, which will contribute to increased transparency and predictability of decision-making processes. Last but not least, the comparison of groups of legal texts (clustering) will facilitate the navigation of extensive legal information, which is priceless for both professionals and ordinary users seeking relevant legal information. The project results will be published in renowned scientific journals, as well as at conferences and workshops organized by the project team. " Our university covers the issue of machine learning methods and their use in the analysis of legal texts with great scientific expertise, which is proven by several projects we have implemented. The project provides us with another opportunity to use the latest machine learning methods on legal texts, which will significantly increase the efficiency and accuracy of their analysis," said Assoc. Prof. Pavol Sokol, PhD. et PhD., the project’s expert guarantor and associate professor at the Institute of Informatics, Faculty of Science, UPJŠ. "The project provides an opportunity for legal researchers to engage in excellent research and gain valuable experience in the field of legal text analysis using machine learning methods. Participation in the research team, that is composed of computer scientists and representatives of the commercial sector, will contribute to the development of professional skills of our researchers and interdisciplinary understanding of the issues" said Assoc. Prof. Jozef Andraško, PhD., Vice-Dean of PraF UK. "Our company has extensive experience in developing and deploying artificial intelligence tools, as evidenced by the first tool in the ASPI AI system – Samospráva (Self-government), which simplifies working with legislation using the potential of artificial intelligence, and we are intensively working on new tools. We have also integrated four other artificial intelligence tools into our Praetor software, designed for the management of law firms, tax offices, and legal departments. Our practical experience in the deployment of artificial intelligence in legal information systems will connect the latest scientific knowledge with the actual needs of practice," said Ing. Klára Rábel Glosíková, Director of WK.]]> [PraF] Titulka - úzke novinky - z uniba.sk [PraF] EN Titulka - úzke novinky Wed, 05 Mar 2025 14:45:00 +0100