AIMC Topic: Machine Learning

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FedELR: When federated learning meets learning with noisy labels.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Existing research on federated learning (FL) usually assumes that training labels are of high quality for each client, which is impractical in many real-world scenarios (e.g., noisy labels by crowd-sourced annotations), leading to dramatic performanc...
Machine Learning Algorithms Federated Learning Neural Networks, Computer
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FingerPoseNet: A finger-level multitask learning network with residual feature sharing for 3D hand pose estimation.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Hand pose estimation approaches commonly rely on shared hand feature maps to regress the 3D locations of all hand joints. Subsequently, they struggle to enhance finger-level features which are invaluable in capturing joint-to-finger associations and ...
Humans Posture Deep Learning Neural Networks, Computer Hand Imaging, Three-Dimensional Machine Learning Fingers
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ADAMT: Adaptive distributed multi-task learning for efficient image recognition in Mobile Ad-hoc Networks.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Distributed machine learning in mobile adhoc networks faces significant challenges due to the limited computational resources of devices, non-IID data distribution, and dynamic network topology. Existing approaches often rely on centralized coordinat...
Image Processing, Computer-Assisted Pattern Recognition, Automated Machine Learning Algorithms Neural Networks, Computer Humans
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DFT-assisted machine learning for polyester membrane design in textile wastewater recovery applications.

Water research Jul 1, 2025
Resource recovery from textile wastewater has attracted increasing interest because it simultaneously addresses wastewater treatment and maximizes the utilization of the residual dyes. Although polyester membranes have demonstrated great potential fo...
Water Pollutants, Chemical Density Functional Theory Water Purification Waste Disposal, Fluid Membranes, Artificial Textiles Coloring Agents Polyesters Machine Learning Wastewater
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Complex quantized minimum error entropy with fiducial points: theory and application in model regression.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Minimum error entropy with fiducial points (MEEF) has gained significant attention due to its excellent performance in mitigating the adverse effects of non-Gaussian noise in the fields of machine learning and signal processing. However, the original...
Algorithms Regression Analysis Neural Networks, Computer Entropy Humans Machine Learning
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Learn the global prompt in the low-rank tensor space for heterogeneous federated learning.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Federated learning collaborates with multiple clients to train a global model, enhancing the model generalization while allowing the local data transmission-free and security. However, federated learning currently faces three intractable challenges: ...
Learning Machine Learning Federated Learning Algorithms Humans Neural Networks, Computer
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StoCFL: A stochastically clustered federated learning framework for Non-IID data with dynamic client participation.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Federated learning is a distributed learning framework that takes full advantage of private data samples kept on edge devices. In real-world federated learning systems, these data samples are often decentralized and Non-Independently Identically Dist...
Algorithms Cluster Analysis Neural Networks, Computer Machine Learning Stochastic Processes Federated Learning Humans
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Continual learning of conjugated visual representations through higher-order motion flows.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Learning with neural networks from a continuous stream of visual information presents several challenges due to the non-i.i.d. nature of the data. However, it also offers novel opportunities to develop representations that are consistent with the inf...
Humans Neural Networks, Computer Machine Learning Motion
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DRTN: Dual Relation Transformer Network with feature erasure and contrastive learning for multi-label image classification.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
The objective of multi-label image classification (MLIC) task is to simultaneously identify multiple objects present in an image. Several researchers directly flatten 2D feature maps into 1D grid feature sequences, and utilize Transformer encoder to ...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Pattern Recognition, Automated Machine Learning Algorithms
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Approximation by non-symmetric networks for cross-domain learning.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
For the past 30 years or so, machine learning has stimulated a great deal of research in the study of approximation capabilities (expressive power) of a multitude of processes, such as approximation by shallow or deep neural networks, radial basis fu...
Algorithms Machine Learning Humans Neural Networks, Computer
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