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检索条件"主题词=INDUCTIVE LOGIC PROGRAMMING"
524 条 记 录,以下是91-100 订阅
排序:
Mutual Explanations for Cooperative Decision Making in Medicine
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KUNSTLICHE INTELLIGENZ 2020年 第2期34卷 227-233页
作者: Schmid, Ute Finzel, Bettina Univ Bamberg Cognit Syst Bamberg Germany
Exploiting mutual explanations for interactive learning is presented as part of an interdisciplinary research project on transparent machine learning for medical decision support. Focus of the project is to combine de... 详细信息
来源: 评论
Interpreting and predicting social commerce intention based on knowledge graph analysis
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ELECTRONIC COMMERCE RESEARCH 2020年 第1期20卷 197-222页
作者: Yuan, Liu Huang, Zhao Zhao, Wei Stakhiyevich, Pavel Minist Educ Key Lab Modern Teaching Technol Xian Shaanxi Peoples R China Shaanxi Normal Univ Sch Comp Sci 620 West Changan St Xian 710119 Shaanxi Peoples R China
There have been significant efforts to understand, describe, and predict the social commerce intention of users in the areas of social commerce and web data management. Based on recent developments in knowledge graph ... 详细信息
来源: 评论
LazyBum: Decision Tree Learning Using Lazy Propositionalization  1
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29th International Conference on inductive logic programming
作者: Schouterden, Jonas Davis, Jesse Blockeel, Hendrik Katholieke Univ Leuven Dept Comp Sci Celestijnenlaan 200ABox 2402 B-3001 Leuven Belgium
Propositionalization is the process of summarizing relational data into a tabular (attribute-value) format. The resulting table can next be used by any propositional learner. This approach makes it possible to apply a... 详细信息
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Phase Transition and New Fitness Function Based Genetic inductive logic programming Algorithm
Phase Transition and New Fitness Function Based Genetic Indu...
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IEEE Congress on Evolutionary Computation (CEC)
作者: Li, Yanjuan Guo, Maozu Harbin Inst Technol Sch Comp Sci & Technol Harbin 150006 Peoples R China
A new genetic inductive logic programming (GILP for short) algorithm named PT-NFF-GILP (Phase Transition and New Fitness Function based Genetic inductive logic programming) is proposed in this paper. Based on phase tr... 详细信息
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White-box Induction From SVM Models: Explainable AI with logic programming
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THEORY AND PRACTICE OF logic programming 2020年 第5期20卷 656-670页
作者: Shakerin, Farhad Gupta, Gopal Univ Texas Dallas Richardson TX 75083 USA
We focus on the problem of inducing logic programs that explain models learned by the support vector machine (SVM) algorithm. The top-down sequential covering inductive logic programming (ILP) algorithms (e.g., FOIL) ... 详细信息
来源: 评论
Learning Parsers for Technical Drawings  19th
Learning Parsers for Technical Drawings
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European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)
作者: Van Daele, Dries Decleyre, Nicholas Dubois, Herman Meert, Wannes Katholieke Univ Leuven Dept CS Leuven Belgium St Gobain Mobil Engn Components Seals Kontich Belgium
From a set of technical drawings, we learn a parser program to interpret the tabular data contained in such a drawing. This enables automatic reasoning and learning on top of a database of technical drawings. For exam... 详细信息
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Toward a Neural-Symbolic Framework for Automated Workflow Analysis in Surgery  15th
Toward a Neural-Symbolic Framework for Automated Workflow An...
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15th Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON)
作者: Nakawala, Hirenkumar De Momi, Elena Bianchi, Roberto Catellani, Michele De Cobelli, Ottavio Jannin, Pierre Ferrigno, Giancarlo Fiorini, Paolo Univ Verona Dept Comp Sci Via Str Grazie 15 I-37134 Verona Italy Politecn Milan Dept Elect Informat & Bioengn DEIB Piazza Leonardo da Vinci 32 I-20133 Milan Italy European Inst Oncol Dept Urol Via Guiseppe Ripamonti 435 I-20141 Milan Italy Univ Rennes 1 LTSI INSERM U1099 F-35000 Rennes France
Learning production rules from continuous data streams, e.g. surgical videos, is a challenging problem. To learn production rules, we present a novel framework consisting of deep learning models and inductive logic pr... 详细信息
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From Reinforcement Learning Towards Artificial General Intelligence  8th
From Reinforcement Learning Towards Artificial General Intel...
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World Conference on Information Systems and Technologies (WorldCIST)
作者: Rocha, Filipe Marinho Costa, Vitor Santos Reis, Luis Paulo Univ Porto FCUP Fac Ciencias Porto Portugal Univ Porto FEUP Fac Engn Porto Portugal Univ Porto LIACC Lab Inteligencia Artificial & Ciencia Compu Porto Portugal INESCTEC CRACS Ctr Adv Comp Syst Porto Portugal
The present work surveys research that integrates successfully a number of complementary fields in Artificial Intelligence. Starting from integrations in Reinforcement Learning: Deep Reinforcement Learning and Relatio... 详细信息
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Ontology-Based Skill Description Learning for Flexible Production Systems  25
Ontology-Based Skill Description Learning for Flexible Produ...
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25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
作者: Himmelhuher, Anna Grimm, Stephan Runkler, Thomas Zillner, Sonja Siemens AG Munich Germany
The increasing importance of resource-efficient production entails that manufacturing companies have to create a more dynamic production environment, with flexible manufacturing machines and processes. To fully utiliz... 详细信息
来源: 评论
White-box Induction From SVM Models: Explainable AI with logic programming
White-box Induction From SVM Models: Explainable AI with Log...
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36th International Conference on logic programming (ICLP)
作者: Shakerin, Farhad Gupta, Gopal Univ Texas Dallas Richardson TX 75083 USA
We focus on the problem of inducing logic programs that explain models learned by the support vector machine (SVM) algorithm. The top-down sequential covering inductive logic programming (ILP) algorithms (e.g., FOIL) ... 详细信息
来源: 评论