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A multi-source heterogeneous medical data enhancement framework based on lakehouse
Obtaining high-quality data sets from raw data is a key step before data exploration and analysis. Nowadays, in the medical domain, a large amount of...
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AFL-HCS: asynchronous federated learning based on heterogeneous edge client selection
Federated learning (FL) constitutes a potent machine learning paradigm extensively applied in edge computing for training models on vast datasets....
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A heterogeneous graph-based semi-supervised learning framework for access control decision-making
For modern information systems, robust access control mechanisms are vital in safeguarding data integrity and ensuring the entire system’s security....
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Fast computation of General SimRank on heterogeneous information network
Similarity computation is a fundamental aspect of information network analysis, underpinning many research tasks including information retrieval,...
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Unraveling the complexities of a highly heterogeneous aquifer under convergent radial flow conditions
Untangling flow and mass transport in aquifers is essential for effective water management and protection. However, understanding the mechanisms...
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HeterMM: applying in-DRAM index to heterogeneous memory-based key-value stores
We propose HeterMM, a versatile framework that leverages in-DRAM indexes in KV stores on heterogeneous memory. HeterMM incorporates a plug-in...
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Scheduling Fork-Joins to Heterogeneous Processors
The scheduling of task graphs with communication delays has been extensively studied. Recently, new results for the common sub-case of fork-join...
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Diversified recommendation using implicit content node embedding in heterogeneous information network
Many approaches based on Graph Neural Networks (GNNs) have been proposed to identify relationships between users and items while modelling user...
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Programming Heterogeneous Architectures Using Hierarchical Tasks
Task-based systems have gained popularity as they promise to exploit the computational power of complex heterogeneous systems. A common programming...
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Deep neural network learning for power limited heterogeneous system with workload classification
Heterogeneous systems providing diverse computational capabilities have unlocked a new pathway in multicore processors. The versatility in...
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Intelligent resource optimization for scalable and energy-efficient heterogeneous IoT devices
Due to resource shortages and device diversity, energy efficiency and scalability issues are critical in the Internet of Things (IoT) space. Managing...
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MT-office: parallel password recovery program for office on domestic heterogeneous multi-core processor
With the improvement of security awareness, in order to guarantee information security, more advanced and secure encryption algorithms are applied to...
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LBB: load-balanced batching for efficient distributed learning on heterogeneous GPU cluster
As the cost of deep learning training increases, using heterogeneous GPU clusters is a reasonable way to scale cluster resources to support...
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Heterogeneous Signal Identification
In this chapter, we will present the motivation of signal identification for cross-technology coexistence, then elaborate our system design which...
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Traffic Offloading in Heterogeneous Networks
In heterogeneous ultra-dense networks (HetUDNs), the software-defined wireless network (SDWN) separates resource management from geo-distributed...
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Learning heterogeneous subgraph representations for team discovery
The team discovery task is concerned with finding a group of experts from a collaboration network who would collectively cover a desirable set of...
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Systems with Heterogeneous Workloads
Today’s workloads consist of applications having very different characteristics in terms of service requirements, performance objectives, and arrival...
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Adaptive device sampling and deadline determination for cloud-based heterogeneous federated learning
As a new approach to machine learning, Federated learning enables distributned traiing on edge devices and aggregates local models into a global...
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Resource allocation in heterogeneous network with node and edge enhanced graph attention network
In wireless networks, the effectiveness of beamforming and power allocation strategies is crucial in meeting the increasing data demands of users and...
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Configuration optimization for heterogeneous time-sensitive networks
Time-Sensitive Networking (TSN) collectively defines a set of protocols and standard amendments that enhance IEEE 802.1Q Ethernet nodes with...
