Zobrazeno 1 - 10
of 2 744
pro vyhledávání: '"A A, Gorban"'
Erasing a black hole leaves spacetime flat, so light passing through the region before any star forms and after black hole's evaporation shows no time delay, just like a flying mirror that returns to its initial starting point. Quantum radiation from
Externí odkaz:
http://arxiv.org/abs/2411.03521
Autor:
Sutton, Oliver J., Zhou, Qinghua, Wang, Wei, Higham, Desmond J., Gorban, Alexander N., Bastounis, Alexander, Tyukin, Ivan Y.
We reveal the theoretical foundations of techniques for editing large language models, and present new methods which can do so without requiring retraining. Our theoretical insights show that a single metric (a measure of the intrinsic dimension of t
Externí odkaz:
http://arxiv.org/abs/2406.12670
Autor:
Suzen, Neslihan, Mirkes, Evgeny M., Roland, Damian, Levesley, Jeremy, Gorban, Alexander N., Coats, Tim J.
Publikováno v:
2023 IEEE International Conference on Big Data (BigData), 4979-4986
Electronic patient records (EPRs) produce a wealth of data but contain significant missing information. Understanding and handling this missing data is an important part of clinical data analysis and if left unaddressed could result in bias in analys
Externí odkaz:
http://arxiv.org/abs/2402.06563
Autor:
Tyukin, Ivan Y., Tyukina, Tatiana, van Helden, Daniel, Zheng, Zedong, Mirkes, Evgeny M., Sutton, Oliver J., Zhou, Qinghua, Gorban, Alexander N., Allison, Penelope
We present a new methodology for handling AI errors by introducing weakly supervised AI error correctors with a priori performance guarantees. These AI correctors are auxiliary maps whose role is to moderate the decisions of some previously construct
Externí odkaz:
http://arxiv.org/abs/2402.00899
In principle, the local classification of spacetimes is always possible using the Cartan-Karlhede algorithm. However, in practice, the process of determining equivalence of two spacetimes is potentially computationally difficult or not at all possibl
Externí odkaz:
http://arxiv.org/abs/2312.11433
Autor:
Kastalskiy, Innokentiy, Zinovyev, Andrei, Mirkes, Evgeny, Kazantsev, Victor, Gorban, Alexander N.
Publikováno v:
Communications in Nonlinear Science and Numerical Simulation, Volume 132, May 2024, 107906
In the context of natural disasters, human responses inevitably intertwine with natural factors. The COVID-19 pandemic, as a significant stress factor, has brought to light profound variations among different countries in terms of their adaptive dyna
Externí odkaz:
http://arxiv.org/abs/2311.13917
Publikováno v:
Artificial Neural Networks and Machine Learning ICANN 2023. Lecture Notes in Computer Science, vol 14254, pp 516-529. Springer, Cham
High dimensional data can have a surprising property: pairs of data points may be easily separated from each other, or even from arbitrary subsets, with high probability using just simple linear classifiers. However, this is more of a rule of thumb t
Externí odkaz:
http://arxiv.org/abs/2311.07579
Autor:
Quanming Wu, O. A. Gorban
Publikováno v:
Научный диалог, Vol 13, Iss 9, Pp 169-187 (2024)
This article presents a comprehensive analysis of the phraseological units ‘staryy volk’ [old wolf], ‘travlenyy volk’ [tricked wolf], ‘morskoy volk’ [sea wolf], ‘volkom vyt'’ [to howl like a wolf], and ‘khot' volkom voy’ [you migh
Externí odkaz:
https://doaj.org/article/477e1754ff7f494b835f9dc39081143e
Autor:
Bastounis, Alexander, Gorban, Alexander N., Hansen, Anders C., Higham, Desmond J., Prokhorov, Danil, Sutton, Oliver, Tyukin, Ivan Y., Zhou, Qinghua
In this work, we assess the theoretical limitations of determining guaranteed stability and accuracy of neural networks in classification tasks. We consider classical distribution-agnostic framework and algorithms minimising empirical risks and poten
Externí odkaz:
http://arxiv.org/abs/2309.07072
Autor:
Sutton, Oliver J., Zhou, Qinghua, Tyukin, Ivan Y., Gorban, Alexander N., Bastounis, Alexander, Higham, Desmond J.
Adversarial attacks dramatically change the output of an otherwise accurate learning system using a seemingly inconsequential modification to a piece of input data. Paradoxically, empirical evidence indicates that even systems which are robust to lar
Externí odkaz:
http://arxiv.org/abs/2309.03665