Results 21 to 30 of about 927,930 (289)
Normal Forms of Conditional Belief Bases Respecting Inductive Inference
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 Normal forms of syntactic entities play an important role in many different areas in computer science. In this paper, we address the question of how to obtain normal forms and minimal normal forms of conditional belief bases in order to, e.g., ease ...
Christoph Beierle, Jonas Haldimann
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InGram: Inductive Knowledge Graph Embedding via Relation Graphs [PDF]
International Conference on Machine Learning, 2023 Inductive knowledge graph completion has been considered as the task of predicting missing triplets between new entities that are not observed during training.
Jaejun Lee +2 more
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The Consumer Contextual Decision-Making Model
Frontiers in Psychology, 2020 Consumers can have difficulty expressing their buying intentions on an explicit level. The most common explanation for this intention-action gap is that consumers have many cognitive biases that interfere with rational decision-making.
Jyrki Suomala
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Lubelski Rocznik Pedagogiczny, 2021 Introduction: At the beginning of the cognitive procedure, the choice of the research perspective is crucial. Whereas, in numerous pedagogy-field publications, authors almost automatically move from the problem to the methods and techniques of its ...
Małgorzata Makiewicz
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New Developments in Chinese Studies of Contemporary Inductive Logic
Asian Studies, 2022 Contemporary Chinese studies in inductive logic have long revolved around the unfolding of a philosophical investigation into Hume’s problem. Led by research in probabilistic logic, the principal content of contemporary Chinese logic consists of ...
Xiaoming Ren
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Graph Condensation for Inductive Node Representation Learning [PDF]
IEEE International Conference on Data Engineering, 2023 Graph neural networks (GNNs) encounter significant computational challenges when handling large-scale graphs, which severely restricts their efficacy across diverse applications.
Xin Gao +6 more
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On the complexity of inductive inference
Information and Control, 1986 A notion of the complexity of the inference process with some examples of trade-offs between the complexity of an inference and the accuracy of the results are presented in the paper. The complexity measures are based on the total resources used by an inference strategy in the process of converging to a correct inference. Some examples of the effect of
Robert P. Daley, Carl H. Smith
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The communication of inductive inferences [PDF]
, 1997 We propose a new approach to communication between agents that perform inductive inference. Consider a community of agents where each agent has a limited view of the overall world. When an agent in this community induces a hypothesis about the world, it necessarily reflects that agent's partial view of the world.
Winton Davies, Peter Edwards
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Maximum Entropy in Drug Discovery
Entropy, 2014 Drug discovery applies multidisciplinary approaches either experimentally, computationally or both ways to identify lead compounds to treat various diseases. While conventional approaches have yielded many US Food and Drug Administration (FDA)-approved
Chih-Yuan Tseng, Jack Tuszynski
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Brain Imaging, Forward Inference, and Theories of Reasoning
Frontiers in Human Neuroscience, 2015 This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006).
Evan eHeit
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