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Titlebook: New Frontiers in Artificial Intelligence; JSAI-isAI Internatio Maki Sakamoto,Naoaki Okazaki,Ken Satoh Conference proceedings 2020 The Edito

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11#
發(fā)表于 2025-3-23 10:10:17 | 只看該作者
test Common Supersequence (WSCS) problem, introduced by Amir et al. [SPIRE 2011], that is, the SCS problem on weighted strings. In the WSCS problem, we are given two weighted strings . and . and a threshold . on probability, and we are asked to compute the shortest (standard) string . such that both
12#
發(fā)表于 2025-3-23 16:32:45 | 只看該作者
13#
發(fā)表于 2025-3-23 18:21:10 | 只看該作者
Paul M. Pietroskitest Common Supersequence (WSCS) problem, introduced by Amir et al. [SPIRE 2011], that is, the SCS problem on weighted strings. In the WSCS problem, we are given two weighted strings . and . and a threshold . on probability, and we are asked to compute the shortest (standard) string . such that both
14#
發(fā)表于 2025-3-23 23:54:58 | 只看該作者
Jan K?pping,Thomas Ede Zimmermannrom learning-to-rank models. The method takes two steps - estimating click propensities and using them to train unbiased models. Most common methods proposed in the literature for estimating propensities involve some degree of intervention in the live search engine. An alternative approach proposed
15#
發(fā)表于 2025-3-24 05:10:14 | 只看該作者
Alastair Butlernode paths). A . is a regular language admitting an accepting Wheeler automaton. Wheeler languages admit efficient and elegant solutions to hard problems such as automata compression and regular expression matching, therefore deciding whether a regular language is Wheeler is relevant in applications
16#
發(fā)表于 2025-3-24 10:09:49 | 只看該作者
17#
發(fā)表于 2025-3-24 13:15:18 | 只看該作者
Oleg Kiselyov,Yuya Hoshinoon of this distance, which is simply the minimum number of character insertions, deletions and substitutions needed to transform one string to the other, presents remarkable algorithmic challenges..This talk will examine the task of approximating the basic edit distance between two strings, starting
18#
發(fā)表于 2025-3-24 16:57:42 | 只看該作者
19#
發(fā)表于 2025-3-24 20:52:23 | 只看該作者
20#
發(fā)表于 2025-3-25 01:23:38 | 只看該作者
PatentTransformer-1.5: Measuring Patent Claim Generation by Span Relevancyalize “augmented inventing” for inventors by leveraging new Deep Learning techniques. We envision the possibility of building an “auto-complete” function for inventors to conceive better inventions in the era of artificial intelligence. In order to generate patent claims with reasonable quality, a f
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