Zobrazeno 1 - 10
of 12 613
pro vyhledávání: '"A. A. Melnyk"'
Graph augmentation is a fundamental and well-studied problem that arises in network optimization. We consider a new variant of this model motivated by reconfigurable communication networks. In this variant, we consider a given physical network and th
Externí odkaz:
http://arxiv.org/abs/2411.11426
Peer review, as a widely used practice to ensure the quality and integrity of publications, lacks a well-defined and common mechanism to self-incentivize virtuous behavior across all the conferences and journals. This is because information about rev
Externí odkaz:
http://arxiv.org/abs/2411.08450
A wide variety of biomedical image data, as well as methods for generating training images using basic deep neural networks, were analyzed. Additionally, all platforms for creating images were analyzed, considering their characteristics. The article
Externí odkaz:
http://arxiv.org/abs/2405.16119
Publikováno v:
ICDCS 2024
In the well-known Minimum Linear Arrangement problem (MinLA), the goal is to arrange the nodes of an undirected graph into a permutation so that the total stretch of the edges is minimized. This paper studies an online (learning) variant of MinLA whe
Externí odkaz:
http://arxiv.org/abs/2405.15963
Among lattice configurations of densely packed hard ellipses, Monte Carlo simulations are used to identify the so-called parallel and diagonal lattices as the two favourable states. The free energies of these two states are computed for several syste
Externí odkaz:
http://arxiv.org/abs/2403.17194
High-dimensional real-world systems can often be well characterized by a small number of simultaneous low-complexity interactions. The analysis of variance (ANOVA) decomposition and the anchored decomposition are typical techniques to find sparse add
Externí odkaz:
http://arxiv.org/abs/2403.15563
Autor:
Das, Payel, Chaudhury, Subhajit, Nelson, Elliot, Melnyk, Igor, Swaminathan, Sarath, Dai, Sihui, Lozano, Aurélie, Kollias, Georgios, Chenthamarakshan, Vijil, Jiří, Navrátil, Dan, Soham, Chen, Pin-Yu
Efficient and accurate updating of knowledge stored in Large Language Models (LLMs) is one of the most pressing research challenges today. This paper presents Larimar - a novel, brain-inspired architecture for enhancing LLMs with a distributed episod
Externí odkaz:
http://arxiv.org/abs/2403.11901
Autor:
Akbari, Amirreza, Coiteux-Roy, Xavier, d'Amore, Francesco, Gall, François Le, Lievonen, Henrik, Melnyk, Darya, Modanese, Augusto, Pai, Shreyas, Renou, Marc-Olivier, Rozhoň, Václav, Suomela, Jukka
We connect three distinct lines of research that have recently explored extensions of the classical LOCAL model of distributed computing: A. distributed quantum computing and non-signaling distributions [e.g. STOC 2024], B. finitely-dependent process
Externí odkaz:
http://arxiv.org/abs/2403.01903
Autor:
Fritze, Martin P. (AUTHOR) martinpaul.fritze@zu.de, Völckner, Franziska (AUTHOR), Melnyk, Valentyna (AUTHOR)
Publikováno v:
Journal of Marketing. Jul2024, Vol. 88 Issue 4, p22-39. 18p.
Autor:
Apostolov, S. S., Usatenko, O. V., Yampol'skii, V. A., Melnyk, S. S., Grigolini, P., Krokhin, A.
We study two-state (dichotomous, telegraph) random ergodic continuous-time processes with dynamics depending on their past. We take into account the history of process in an explicit form by introducing an integral non-local memory term into the cond
Externí odkaz:
http://arxiv.org/abs/2402.11038