bile648 发表于 2025-3-27 00:56:55
http://reply.papertrans.cn/47/4639/463887/463887_31.png雄辩 发表于 2025-3-27 02:35:39
Francesca A. Lisi,Umberto Stracciature for critical and non-critical applications. This reduces the effort to implement and to manage different communication architectures. The present work develops and evaluates methods and procedures that enable high reliable communication between two endpoints over several shared telecommunicatiovisceral-fat 发表于 2025-3-27 08:55:24
orm these regularly. These methods however require a lot of time and effort to complete. A solution to this problem would be combining the assessments. This requires that proper safety and security analysis methods must be selected – those that have compatible elements..In this paper we propose a me泰然自若 发表于 2025-3-27 12:53:29
http://reply.papertrans.cn/47/4639/463887/463887_34.pngconfederacy 发表于 2025-3-27 15:31:57
http://reply.papertrans.cn/47/4639/463887/463887_35.png表皮 发表于 2025-3-27 20:36:48
978-3-662-44922-6Springer-Verlag Berlin Heidelberg 2014Boycott 发表于 2025-3-27 22:34:49
http://reply.papertrans.cn/47/4639/463887/463887_37.pngMutter 发表于 2025-3-28 05:09:04
A BDD-Based Algorithm for Learning from Interpretation Transition,tter data structure and an efficient algorithm have been awaited. In this paper, we propose a new learning algorithm of this method utilizing an efficient data structure inspired from Ordered Binary Decision Diagrams. We show empirically that using this representation we can perform the same learning task faster with less memory space.用肘 发表于 2025-3-28 06:37:51
A FOIL-Like Method for Learning under Incompleteness and Vagueness,escription Logics (DLs) have been proposed in the literature. In this paper, we present a novel .-like method for inducing fuzzy DL inclusion axioms from crisp DL knowledge bases and discuss the results obtained on a real-world case study in the tourism application domain also in comparison with related works.法律 发表于 2025-3-28 11:51:53
Conference proceedings 2014cuses on all aspects of learning in logic, multi-relational learning and data mining, statistical relational learning, graph and tree mining, relational reinforcement learning, and other forms of learning from structured data.