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检索条件"主题词=Logic Programs with Annotated Disjunctions"
14 条 记 录,以下是1-10 订阅
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The Most Probable Explanation for Probabilistic logic programs with annotated disjunctions  1
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24th International Conference on Inductive logic Programming (ILP)
作者: Shterionov, Dimitar Renkens, Joris Vlasselaer, Jonas Kimmig, Angelika Meert, Wannes Janssens, Gerda KULeuven Leuven Belgium
Probabilistic logic languages, such as ProbLog and CP-logic, are probabilistic generalizations of logic programming that allow one to model probability distributions over complex, structured domains. Their key probabi... 详细信息
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Reasoning on logic programs with annotated disjunctions
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INTELLIGENZA ARTIFICIALE 2012年 第1期6卷 77-96页
作者: Bragaglia, Stefano Univ Bologna DEIS Viale Risorgimento Bologna Italy
Probabilistic Inductive logic Programming and Statistical Relational Learning are families of techniques that are exploited in Machine Learning applications to perform advanced tasks in several domains. Every day the ... 详细信息
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Summarizing significant subgraphs by probabilistic logic programming
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INTELLIGENT DATA ANALYSIS 2019年 第6期23卷 1299-1312页
作者: Bellodi, Elena Satoh, Ken Sugiyama, Mahito Univ Ferrara Dept Engn Ferrara Italy Natl Inst Informat Tokyo Japan PRESTO JST Tokyo Japan
Although recent advances of significant subgraph mining enable us to find subgraphs that are statistically significantly associated with the class variable from graph databases, it is challenging to interpret the resu... 详细信息
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Approximate Inference for logic programs with annotated disjunctions
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20th International Conference on Inductive logic Programming (ILP)
作者: Bragaglia, Stefano Riguzzi, Fabrizio Univ Ferrara ENDIF Univ Bologna DEIS I-44100 Ferrara Italy
logic programs with annotated disjunctions (LPADs) are a promising language for Probabilistic Inductive logic Programming. In order to develop efficient learning systems for LPADs, it is fundamental to have high-perfo... 详细信息
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Causal inference in cplint
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INTERNATIONAL JOURNAL OF APPROXIMATE REASONING 2017年 91卷 216-232页
作者: Riguzzi, Fabrizio Cota, Giuseppe Bellodi, Elena Zese, Riccardo Univ Ferrara Dipartimento Matemat & Informat Via Saragat 1 I-44122 Ferrara Italy Univ Ferrara Dipartimento Ingn Via Saragat 1 I-44122 Ferrara Italy
cplint is a suite of programs for reasoning and learning with Probabilistic logic Programming languages that follow the distribution semantics. In this paper we describe how we have extended cplint to perform causal r... 详细信息
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SLGAD Resolution for Inference on logic programs with annotated disjunctions
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FUNDAMENTA INFORMATICAE 2010年 第3-4期102卷 429-466页
作者: Riguzzi, Fabrizio Univ Ferrara ENDIF I-44100 Ferrara Italy
logic programs with annotated disjunctions (LPADs) allow to express probabilistic information in logic programming. The semantics of an LPAD is given in terms of the well-founded models of the normal logic programs ob... 详细信息
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Probabilistic logic programming on the web
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SOFTWARE-PRACTICE & EXPERIENCE 2016年 第10期46卷 1381-1396页
作者: Riguzzi, Fabrizio Bellodi, Elena Lamma, Evelina Zese, Riccardo Cota, Giuseppe Univ Ferrara Dipartimento Matemat & Informat I-44100 Ferrara Italy Univ Ferrara Dipartimento Ingn I-44100 Ferrara Italy
We present the web application cplint on SWI-Prolog for SHaring that allows the user to write (SWISH)' Probabilistic logic programs and submit the computation of the probability of queries with a web browser. The ... 详细信息
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Bandit-based Monte-Carlo structure learning of probabilistic logic programs
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MACHINE LEARNING 2015年 第1期100卷 127-156页
作者: Di Mauro, Nicola Bellodi, Elena Riguzzi, Fabrizio Univ Bari Aldo Moro Dipartimento Informat I-70125 Bari Italy Univ Ferrara Dipartimento Ingn I-44122 Ferrara Italy Univ Ferrara Dipartimento Matemat & Informat I-44122 Ferrara Italy
Probabilistic logic programming can be used to model domains with complex and uncertain relationships among entities. While the problem of learning the parameters of such programs has been considered by various author... 详细信息
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Speeding Up Inference for Probabilistic logic programs
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COMPUTER JOURNAL 2014年 第3期57卷 347-363页
作者: Riguzzi, Fabrizio Univ Ferrara Dipartimento Matemat & Informat I-44122 Ferrara Italy
Probabilistic logic Programming (PLP) allows one to represent domains containing many entities connected by uncertain relations and has many applications in particular in Machine Learning. PITA is a PLP algorithm for ... 详细信息
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ALLPAD: approximate learning of logic programs with annotated disjunctions
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MACHINE LEARNING 2008年 第2-3期70卷 207-223页
作者: Riguzzi, Fabrizio Univ Ferrara Dipartimento Ingn I-44100 Ferrara Italy
logic programs with annotated disjunctions (LPADs) provide a simple and elegant framework for representing probabilistic knowledge in logic programming. In this paper we consider the problem of learning ground LPADs s... 详细信息
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