5 Result(s)
within
Zimu Zhou
Computer Science
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Chapter and Conference Paper
Approximate k-Nearest Neighbor Query over Spatial Data Federation
Approximate nearest neighbor query is a fundamental spatial query widely applied in many real-world applications. In the big data era, there is an increasing demand to scale these queries over a spatial data f...
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Chapter and Conference Paper
Data Source Selection in Federated Learning: A Submodular Optimization Approach
Federated learning is a new learning paradigm that jointly trains a model from multiple data sources without sharing raw data. For the practical deployment of federated learning, data source selection is compu...
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Chapter
Efficient and Fair Data Valuation for Horizontal Federated Learning
Availability of big data is crucial for modern machine learning applications and services. Federated learning is an emerging paradigm to unite different data owners for machine learning on massive data sets wi...
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Article
Spatial crowdsourcing: a survey
Crowdsourcing is a computing paradigm where humans are actively involved in a computing task, especially for tasks that are intrinsically easier for humans than for computers. Spatial crowdsourcing is an incre...
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Chapter and Conference Paper
Multi-Worker-Aware Task Planning in Real-Time Spatial Crowdsourcing
Spatial crowdsourcing emerges as a new computing paradigm with the development of mobile Internet and the ubiquity of mobile devices. The core of many real-world spatial crowdsourcing applications is to assign...
