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pro vyhledávání: '"RON, M."'
Nearly perfect packing codes are those codes that meet the Johnson upper bound on the size of error-correcting codes. This bound is an improvement to the sphere-packing bound. A related bound for covering codes is known as the van Wee bound. Codes th
Externí odkaz:
http://arxiv.org/abs/2405.00258
Autor:
Wei, Hengjia, Roth, Ron M.
Error-correcting codes over the real field are studied which can locate outlying computational errors when performing approximate computing of real vector--matrix multiplication on resistive crossbars. Prior work has concentrated on locating a single
Externí odkaz:
http://arxiv.org/abs/2402.13503
We prove that, for any integer $k$, the $k$-th root enumerator in the classical Weyl group of type $D$ is a proper character. The proof uses higher Lie characters of type $B$.
Comment: 35 pages, minor changes, to appear in J. Algebra
Comment: 35 pages, minor changes, to appear in J. Algebra
Externí odkaz:
http://arxiv.org/abs/2312.08904
Autor:
Zhao, Lei, Buonanno, Luca, Roth, Ron M., Serebryakov, Sergey, Gajjar, Archit, Moon, John, Ignowski, Jim, Pedretti, Giacomo
Transformer models represent the cutting edge of Deep Neural Networks (DNNs) and excel in a wide range of machine learning tasks. However, processing these models demands significant computational resources and results in a substantial memory footpri
Externí odkaz:
http://arxiv.org/abs/2312.06532
Autor:
Roth, Ron M.
Let $[q\rangle$ denote the integer set $\{0,1,\ldots,...,q-1\}$ and let $\mathbb{B}=\{0,1\}$. The problem of implementing functions $[q\rangle\rightarrow\mathbb{B}$ on content-addressable memories (CAMs) is considered. CAMs can be classified by the i
Externí odkaz:
http://arxiv.org/abs/2305.13159
Autor:
Pedretti, Giacomo, Moon, John, Bruel, Pedro, Serebryakov, Sergey, Roth, Ron M., Buonanno, Luca, Gajjar, Archit, Ziegler, Tobias, Xu, Cong, Foltin, Martin, Faraboschi, Paolo, Ignowski, Jim, Graves, Catherine E.
Structured, or tabular, data is the most common format in data science. While deep learning models have proven formidable in learning from unstructured data such as images or speech, they are less accurate than simpler approaches when learning from t
Externí odkaz:
http://arxiv.org/abs/2304.01285
Autor:
Adin, Ron M., Roichman, Yuval
A new descent set statistic on involutions, defined geometrically via their interpretation as matchings, is introduced in this paper, and shown to be equi-distributed with the standard one. This concept is then applied to construct explicit cyclic de
Externí odkaz:
http://arxiv.org/abs/2210.14839
Publikováno v:
In Journal of Algebra 15 February 2025 664 Part B:26-72
Autor:
Giacomo Pedretti, John Moon, Pedro Bruel, Sergey Serebryakov, Ron M. Roth, Luca Buonanno, Archit Gajjar, Lei Zhao, Tobias Ziegler, Cong Xu, Martin Foltin, Paolo Faraboschi, Jim Ignowski, Catherine E. Graves
Publikováno v:
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, Vol 10, Pp 116-124 (2024)
Structured, or tabular, data are the most common format in data science. While deep learning models have proven formidable in learning from unstructured data such as images or speech, they are less accurate than simpler approaches when learning from
Externí odkaz:
https://doaj.org/article/a602a5141d5341bda6924b89239da5ec