底的根除
发表于 2025-3-21 17:34:40
书目名称Inductive Logic Programming影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0463902<br><br> <br><br>书目名称Inductive Logic Programming影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0463902<br><br> <br><br>书目名称Inductive Logic Programming网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0463902<br><br> <br><br>书目名称Inductive Logic Programming网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0463902<br><br> <br><br>书目名称Inductive Logic Programming被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0463902<br><br> <br><br>书目名称Inductive Logic Programming被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0463902<br><br> <br><br>书目名称Inductive Logic Programming年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0463902<br><br> <br><br>书目名称Inductive Logic Programming年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0463902<br><br> <br><br>书目名称Inductive Logic Programming读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0463902<br><br> <br><br>书目名称Inductive Logic Programming读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0463902<br><br> <br><br>
扫兴
发表于 2025-3-21 23:33:24
,Regularization in Probabilistic Inductive Logic Programming,erform inference in a lifted way. LIFTCOVER is an algorithm used to perform parameter and structure learning of liftable probabilistic logic programs. In particular, it performs parameter learning via Expectation Maximization and LBFGS. In this paper, we present an updated version of LIFTCOVER, call
Anticlimax
发表于 2025-3-22 02:49:07
Towards ILP-Based , Passive Learning,inatorial nature of the problem, current state-of-the-art solutions are based on exhaustive search. They use an example at the time to discard a single candidate formula at the time, instead of exploiting the full set of examples to prune the search space. This hinders their applicability when examp
陶醉
发表于 2025-3-22 05:00:02
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BLANC
发表于 2025-3-22 10:02:16
,Select First, Transfer Later: Choosing Proper Datasets for Statistical Relational Transfer Learningtional and rich probability structures. Although SRL techniques have succeeded in many real-world applications, they follow the same assumption as most ML techniques by assuming training and testing data have the same distribution and are sampled from the same feature space. Changes between these di
被告
发表于 2025-3-22 14:12:58
,GNN Based Extraction of Minimal Unsatisfiable Subsets,atisfiability which, as a result, have been used in various applications. Although various systematic algorithms for the extraction of MUSes have been proposed, few heuristic methods have been studied, as the process of designing efficient heuristics requires extensive experience and expertise. In t
胆小懦夫
发表于 2025-3-22 17:05:30
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和音
发表于 2025-3-23 00:18:23
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知识分子
发表于 2025-3-23 02:41:54
,An Experimental Overview of Neural-Symbolic Systems,, more and more researchers have encountered the limitations of deep learning, which has led to a rise in the popularity of neural-symbolic AI, with a wide variety of systems being developed. However, many of these systems are either evaluated on different benchmarks, or introduce new benchmarks tha
CAGE
发表于 2025-3-23 08:19:25
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