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of 2 229
pro vyhledávání: '"SAKAMOTO, HIROSHI"'
Autor:
Nonaka, Keita, Yamanouchi, Kazutaka, I, Tomohiro, Okita, Tsuyoshi, Shimada, Kazutaka, Sakamoto, Hiroshi
Publikováno v:
Electronics 11(7), Article number 1014, 2022
In this study, we propose a simple and effective preprocessing method for subword segmentation based on a data compression algorithm. Compression-based subword segmentation has recently attracted significant attention as a preprocessing method for tr
Externí odkaz:
http://arxiv.org/abs/2202.13590
Publikováno v:
Algorithms 15(7), Article number 229, 2022
For the feature selection problem, we propose an efficient privacy-preserving algorithm. Let $D$, $F$, and $C$ be data, feature, and class sets, respectively, where the feature value $x(F_i)$ and the class label $x(C)$ are given for each $x\in D$ and
Externí odkaz:
http://arxiv.org/abs/2110.05088
Publikováno v:
In Autonomic Neuroscience: Basic and Clinical June 2024 253
Autor:
Yoshimoto, Yohei, Kataoka, Masaharu, Takabatake, Yoshimasa, I, Tomohiro, Shin, Kilho, Sakamoto, Hiroshi
We consider an efficient two-party protocol for securely computing the similarity of strings w.r.t. an extended edit distance measure. Here, two parties possessing strings $x$ and $y$, respectively, want to jointly compute an approximate value for $\
Externí odkaz:
http://arxiv.org/abs/1911.10719
Autor:
Gagie, Travis, I, Tomohiro, Manzini, Giovanni, Navarro, Gonzalo, Sakamoto, Hiroshi, Benkner, Louisa Seelbach, Takabatake, Yoshimasa
Grammar-based compression is a popular and powerful approach to compressing repetitive texts but until recently its relatively poor time-space trade-offs during real-life construction made it impractical for truly massive datasets such as genomic dat
Externí odkaz:
http://arxiv.org/abs/1910.07145
Autor:
Gagie, Travis, I, Tomohiro, Manzini, Giovanni, Navarro, Gonzalo, Sakamoto, Hiroshi, Takabatake, Yoshimasa
Data compression is a powerful tool for managing massive but repetitive datasets, especially schemes such as grammar-based compression that support computation over the data without decompressing it. In the best case such a scheme takes a dataset so
Externí odkaz:
http://arxiv.org/abs/1906.00809
Autor:
Sakai, Kensuke, Ohno, Tatsuya, Goto, Keisuke, Takabatake, Yoshimasa, I, Tomohiro, Sakamoto, Hiroshi
Given a string $T$ of length $N$, the goal of grammar compression is to construct a small context-free grammar generating only $T$. Among existing grammar compression methods, RePair (recursive paring) [Larsson and Moffat, 1999] is notable for achiev
Externí odkaz:
http://arxiv.org/abs/1811.01472
Run-length encoding Burrows-Wheeler Transformed strings, resulting in Run-Length BWT (RLBWT), is a powerful tool for processing highly repetitive strings. We propose a new algorithm for online RLBWT working in run-compressed space, which runs in $O(n
Externí odkaz:
http://arxiv.org/abs/1704.05233
Various grammar compression algorithms have been proposed in the last decade. A grammar compression is a restricted CFG deriving the string deterministically. An efficient grammar compression develops a smaller CFG by finding duplicated patterns and
Externí odkaz:
http://arxiv.org/abs/1607.04446
Although several self-indexes for highly repetitive text collections exist, developing an index and search algorithm with editing operations remains a challenge. Edit distance with moves (EDM) is a string-to-string distance measure that includes subs
Externí odkaz:
http://arxiv.org/abs/1602.06688