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Titlebook: Inductive Logic Programming; 19th International C Luc Raedt Conference proceedings 2010 Springer-Verlag Berlin Heidelberg 2010 Bayesian net

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樓主: 遮陽傘
31#
發(fā)表于 2025-3-26 22:05:29 | 只看該作者
Scott Proper,Prasad Tadepallier encryption) is employed to compute noise for differential privacy by cloud servers to boost efficiency. The proposed scheme allows data providers to outsource their dataset sanitization procedure to cloud service providers with a low communication cost. In addition, the data providers can go offl
32#
發(fā)表于 2025-3-27 03:25:38 | 只看該作者
33#
發(fā)表于 2025-3-27 06:39:59 | 只看該作者
Lothar Richter,Regina Augustin,Stefan Kramerular order we need ...This paper presents a workflow specification and enforcement framework that guarantees the process integrity (for instance, a technical process) by enforcing an access control method that restricts the entities to do only what is allowed in the specified workflow. The framework
34#
發(fā)表于 2025-3-27 11:29:52 | 只看該作者
Knowledge-Directed Theory Revision,xecution of the play and whose skills correspond to making repairs in the goals of the player agents. Our results show effective learning using as few as twenty examples. We also show that structural changes made by such revision can produce performance gains that cannot be matched by doing only numeric optimization.
35#
發(fā)表于 2025-3-27 17:17:07 | 只看該作者
36#
發(fā)表于 2025-3-27 18:58:50 | 只看該作者
37#
發(fā)表于 2025-3-28 00:36:49 | 只看該作者
38#
發(fā)表于 2025-3-28 03:23:17 | 只看該作者
Speeding Up Inference in Statistical Relational Learning by Clustering Similar Query Literals,nt in relational domains to speed up existing inference techniques. Our approach first clusters the query literals and then performs full inference for only one representative from each cluster. The clustering step incurs only a one-time up-front cost when weights are learned over a fixed structure.
39#
發(fā)表于 2025-3-28 06:17:49 | 只看該作者
Boosting First-Order Clauses for Large, Skewed Data Sets,ses used by our modified RankBoost algorithm beyond using individual clauses. We provide results on four large, skewed data sets showing that our modified RankBoost algorithm outperforms the original on area under the recall-precision curves.
40#
發(fā)表于 2025-3-28 10:58:44 | 只看該作者
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