Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Mikhail Belkin"'
Publikováno v:
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 26, Iss 1, Pp 52-59 (2020)
In the paper, we propose, highlight, and discuss a new approach to design full-duplex fiber fronthaul microcell network for a next-generation mobile communication system, for example, incoming 5G NR, using wavelength division multiplexed Radio-over-F
Externí odkaz:
https://doaj.org/article/4932a75be6f44132ac90363dac310ed2
Autor:
Mikhail Tokman, Zhongqu Long, Sultan AlMutairi, Yongrui Wang, Valery Vdovin, Mikhail Belkin, Alexey Belyanin
Publikováno v:
APL Photonics, Vol 4, Iss 3, Pp 034403-034403-8 (2019)
Ultracompact nonlinear optical devices utilizing two-dimensional (2D) materials and nanostructures are emerging as important elements of photonic circuits. Integration of the nonlinear material into a subwavelength cavity or waveguide leads to a stro
Externí odkaz:
https://doaj.org/article/ddc7f7d69557473e91e3a16d4f4effc8
Publikováno v:
PLoS ONE, Vol 9, Iss 5, p e97166 (2014)
A correlation dimension analysis of people's visual experiential streams captured by a smartphone shows that visual experience is two-scaled with a smaller dimension at shorter length scales than at longer length scales. The bend between the two scal
Externí odkaz:
https://doaj.org/article/2cdb45e05fee4054b598e8e2da118331
Publikováno v:
Applied and Computational Harmonic Analysis. 59:85-116
The success of deep learning is due, to a large extent, to the remarkable effectiveness of gradient-based optimization methods applied to large neural networks. The purpose of this work is to propose a modern view and a general mathematical framework
Publikováno v:
Proceedings of the National Academy of Sciences. 120
While neural networks are used for classification tasks across domains, a long-standing open problem in machine learning is determining whether neural networks trained using standard procedures are consistent for classification, i.e., whether such mo
Publikováno v:
Light-Emitting Devices, Materials, and Applications XXVII.
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America
Significance Development of computational models of memory is a subject of long-standing interest at the intersection of machine learning and neuroscience. Our main finding is that overparameterized neural networks trained using standard optimization
Autor:
Mikhail Belkin, Qichao Que
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 42:1856-1867
Radial Basis Function (RBF) networks are a classical family of algorithms for supervised learning. The most popular approach for training RBF networks has relied on kernel methods using regularization based on a norm in a Reproducing Kernel Hilbert S
Autor:
Mikhail Belkin
In the past decade the mathematical theory of machine learning has lagged far behind the triumphs of deep neural networks on practical challenges. However, the gap between theory and practice is gradually starting to close. In this paper I will attem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fd06246e6741813e64646b65f0870ea
http://arxiv.org/abs/2105.14368
http://arxiv.org/abs/2105.14368
Matrix completion problems arise in many applications including recommendation systems, computer vision, and genomics. Increasingly larger neural networks have been successful in many of these applications, but at considerable computational costs. Re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a190be17e1de12e4845b2cd9b02f4fae