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Macsum Aggregation Learning and Missing Values
In recent work, a new kind of aggregation method has been proposed under the name of MacSum aggregation function that can be viewed as an interval...
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Robust Aggregation Function in Federated Learning
Maintaining user data privacy is a crucial challenge for machine learning techniques. Federated learning is a solution that enables machine learning...
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Verifiable Secure Aggregation Protocol Under Federated Learning
Federated learning is a new machine learning paradigm used for collaborative training models among multiple devices. In federated learning, multiple...
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Collective combinatorial optimisation as judgment aggregation
In many settings, a collective decision has to be made over a set of alternatives that has a combinatorial structure: important examples are...
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Multiobjective Rank Aggregation for Gene Prioritization
Rank aggregation involves consolidating multiple individual preference rankings of items to generate a consensus ranking. Typically framed as an...
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BVDFed: Byzantine-resilient and verifiable aggregation for differentially private federated learning
Federated Learning (FL) has emerged as a powerful technology designed for collaborative training between multiple clients and a server while...
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Egalitarian judgment aggregation
Egalitarian considerations play a central role in many areas of social choice theory. Applications of egalitarian principles range from ensuring...
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Aggregation of S-generalized Distances
Aggregation function is a technique of combining a collection of data from several sources into a representative one value. In recent years, fuzzy...
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Half Aggregation Transformer for Exposure Correction
Photos taken under poor illumination conditions often suffer from unsatisfactory visual effects. Recently, Transformer, avoiding the shortcomings of...
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Alleviating Over-Smoothing via Aggregation over Compact Manifolds
Graph neural networks (GNNs) have achieved significant success in various applications. Most GNNs learn the node features with information...
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A global scale comparison of risk aggregation in AI assessment frameworks
AI applications bear inherent risks in various risk dimensions, such as insufficient reliability, robustness, fairness or data protection. It is...
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FedQL: Q-Learning Guided Aggregation for Federated Learning
Federated learning is a distributed machine learning paradigm, which is able to achieve model training without sharing clients’ private data. In each...
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Evaluating explainable social choice-based aggregation strategies for group recommendation
Social choice aggregation strategies have been proposed as an explainable way to generate recommendations to groups of users. However, it is not...
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Decentralized Private Stream Aggregation from Lattices
As various industries and government agencies increasingly seek to build quantum computers, the development of post-quantum constructions for...
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Residual Graph Convolution Collaborative Filtering with Asymmetric neighborhood aggregation
Due to the superior performance of graph convolutional networks (GCNs) in feature extraction and representation, researchers have introduced GCNs to...
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Aggregation-based dual heterogeneous task allocation in spatial crowdsourcing
Spatial crowdsourcing (SC) is a popular data collection paradigm for numerous applications. With the increment of tasks and workers in SC,...
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Exploiting the untapped functional potential of Memento aggregators beyond aggregation
Web archives capture, retain, and present historical versions of web pages. Viewing web archives often amounts to a user visiting the Wayback Machine...
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Fuzzy Logic and Technology, and Aggregation Operators 13th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2023, and 12th International Summer School on Aggregation Operators, AGOP 2023, Palma de Mallorca, Spain, September 4–8, 2023, Proceedings
This book constitutes the proceedings of the 13th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2023, and 12th...
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Feature aggregation and modulation network for single image dehazing
Deep learning-based methods have recently achieved satisfying results in image dehazing. However, we observe that various researchers devote...
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Privacy and integrity-preserving data aggregation scheme for wireless sensor networks digital twins
The security technology of digital twin is an important guarantee to ensure the security of digital twin operation, which mainly includes network...
