Modularity and rigor are two key elements for multi-agent technology. Hong Zhu's multi-agent system (MAS) development method provides proper language facilities supporting modularity. To enhance this method with r...
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Modularity and rigor are two key elements for multi-agent technology. Hong Zhu's multi-agent system (MAS) development method provides proper language facilities supporting modularity. To enhance this method with rigor advocates a DL method to map the specification of MAS into a DL TBox. Thus, we can use the existing DL reasoners and systems to verify and validate some system's properties.
In real life,a large amount of data describing the same learning task may be stored in different institutions(called participants),and these data cannot be shared among par-ticipants due to privacy *** case that diffe...
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In real life,a large amount of data describing the same learning task may be stored in different institutions(called participants),and these data cannot be shared among par-ticipants due to privacy *** case that different attributes/features of the same instance are stored in different institutions is called vertically distributed *** pur-pose of vertical‐federated feature selection(FS)is to reduce the feature dimension of vertical distributed data jointly without sharing local original data so that the feature subset obtained has the same or better performance as the original feature *** solve this problem,in the paper,an embedded vertical‐federated FS algorithm based on particle swarm optimisation(PSO‐EVFFS)is proposed by incorporating evolutionary FS into the SecureBoost framework for the first *** optimising both hyper‐parameters of the XGBoost model and feature subsets,PSO‐EVFFS can obtain a feature subset,which makes the XGBoost model more *** the same time,since different participants only share insensitive parameters such as model loss function,PSO‐EVFFS can effec-tively ensure the privacy of participants'***,an ensemble ranking strategy of feature importance based on the XGBoost tree model is developed to effectively remove irrelevant features on each ***,the proposed algorithm is applied to 10 test datasets and compared with three typical vertical‐federated learning frameworks and two variants of the proposed algorithm with different initialisation ***-mental results show that the proposed algorithm can significantly improve the classifi-cation performance of selected feature subsets while fully protecting the data privacy of all participants.
The W3C recommendation named RIF provides a standard format to facilitate the exchange of rules. After being translated to RIF, the rule language needs a rule engine to perform inference. On the condition that there i...
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In order to fully utilize lesion features and vascular structure and solve the problem of class imbalance, diabetes retinopathy (DR) grading is modeled as a dual-stage task, and the prior-guided dual-stage diabetes re...
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To represent and reason with interval-value information of applications in description logic, based on interval-fuzzy set the classical description logic *** is extended to the fuzzy description logic IFALCN. Its'...
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To represent and reason with interval-value information of applications in description logic, based on interval-fuzzy set the classical description logic *** is extended to the fuzzy description logic IFALCN. Its' syntax, semantics and fuzzy tableau algorithm are presented in detail. Our work enhances the expressiveness and reasoning ability of ALCN. IFALCN is the generalization of fuzzy ALCN based on single value and more expressive than the latter and can conform to human cognition better.
Partially observable Markov decision processes (POMDPs) provide a rich mathematical framework for planning tasks in partially observable stochastic environments. The notion of the covering number, a metric of captur...
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Partially observable Markov decision processes (POMDPs) provide a rich mathematical framework for planning tasks in partially observable stochastic environments. The notion of the covering number, a metric of capturing the search space size of a POMDP planning problem, has been proposed as a complexity measure of approximate POMDP planning. Existing theoretical results are based on POMDPs with finite and discrete state spaces and measured in the l1- metric space. When considering heuristics, they are assumed to be always admissible. This paper extends the theoretical results on the covering numbers of different search spaces, including the newly defined space reachable under inadmissible heuristics, to the ln-metric spaces. We provide a simple but scalable algorithm for estimating covering numbers. Experimentally, we provide estimated covering numbers of the search spaces reachable by following different policies on several benchmark problems, and analyze their abilities to predict the runtime of POMDP planning algorithms.
Medical image registration can establish the spatial consistency of the corresponding anatomical structures between different medical images, which is important in medical image analysis. In recent years, with the rap...
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With the rapid development of information technology, semantic web data present features of massiveness and complexity. As the data-centric science, social computing have great influence in collecting and analyzing se...
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User-specified trust relations are often very sparse and dynamic, making them difficult to accurately predict from online social media. In addition, trust relations are usually unavailable for most social media *** is...
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User-specified trust relations are often very sparse and dynamic, making them difficult to accurately predict from online social media. In addition, trust relations are usually unavailable for most social media *** issues pose a great challenge for predicting trust relations and further building trust networks. In this study,we investigate whether we can predict trust relations via a sparse learning model, and propose to build a trust network without trust relations using only pervasively available interaction data and homophily effect in an online world. In particular, we analyze the reliability of predicting trust relations by interaction behaviors, and provide a principled way to mathematically incorporate interaction behaviors and homophily effect in a novel framework,b Trust. Results of experiments on real-world datasets from Epinions and Ciao demonstrated the effectiveness of the proposed framework. Further experiments were conducted to understand the importance of interaction behaviors and homophily effect in building trust networks.
Focusing on the inversing operation of cardinal directions, the current generative method does not always work correctly. According to the given definitions of smallest rectangular direction and original directions, t...
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