节约
发表于 2025-3-23 13:40:34
Mona Lange,Felix Kuhr,Ralf Möllerternen Herausforderungen, mit denen man konfrontiert ist, kaum beigetragen hat. Das Verhältnis von Aufwand und Ergebnis, so scheint es, fällt mehr als kümmerlich aus. Wahlmüdigkeit, ja eine unverkennbare Politikverdrossenheit sind die Folgen. Eines der Hauptprobleme, die viel beklagte Kluft zwischen
思想流动
发表于 2025-3-23 14:06:15
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/k/image/541645.jpg
格言
发表于 2025-3-23 18:17:02
https://doi.org/10.1007/978-3-319-46073-4human-robot interaction; linear programming; information retrival; machine learning; social robotics; ans
讨人喜欢
发表于 2025-3-24 01:07:24
978-3-319-46072-7Springer International Publishing AG 2016
Tracheotomy
发表于 2025-3-24 02:55:03
KI 2016: Advances in Artificial Intelligence978-3-319-46073-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
Conflagration
发表于 2025-3-24 10:14:17
Using Ontological Knowledge About Active Pharmaceutical Ingredients for a Decision Support System inng the resulting complexity must be able to reason about the respective active ingredients and their interrelationships. In this paper, we present a corresponding ontology and illustrate its use for answering queries relevant for clinical therapy decisions.
Senescent
发表于 2025-3-24 12:15:01
Conference proceedings 2016rreichische Gesellschaft für Artificial Intelligence, ÖGAI, held in Klagenfurt, Austria, in September 2016..The 8 revised full technical papers presented together with 12 technical communications, and 16 extended abstracts were carefully reviewed and selected from 44 submissions..The conference prov
可互换
发表于 2025-3-24 15:55:19
0302-9743 h the Österreichische Gesellschaft für Artificial Intelligence, ÖGAI, held in Klagenfurt, Austria, in September 2016..The 8 revised full technical papers presented together with 12 technical communications, and 16 extended abstracts were carefully reviewed and selected from 44 submissions..The confe
Infect
发表于 2025-3-24 22:05:22
Lifted Junction Tree Algorithmat compactly represent symmetries. First experiments show that we speed up the computation time compared to the propositional version. When querying for multiple marginals, the lifted junction tree algorithm performs better than using lifted VE to infer each marginal individually.
Mercantile
发表于 2025-3-25 00:44:09
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