AIMC Topic: Algorithms

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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: ...
Federated Learning Algorithms Learning Machine Learning Neural Networks, Computer Humans
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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...
Neural Networks, Computer Machine Learning Federated Learning Algorithms Stochastic Processes Cluster Analysis Humans
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Dataset-free weight-initialization on restricted Boltzmann machine.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
In feed-forward neural networks, dataset-free weight-initialization methods such as LeCun, Xavier (or Glorot), and He initializations have been developed. These methods randomly determine the initial values of weight parameters based on specific dist...
Neural Networks, Computer Algorithms Normal Distribution
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PrivCore: Multiplication-activation co-reduction for efficient private inference.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
The marriage of deep neural network (DNN) and secure 2-party computation (2PC) enables private inference (PI) on the encrypted client-side data and server-side models with both privacy and accuracy guarantees, coming at the cost of orders of magnitud...
Privacy Computer Security Algorithms Neural Networks, Computer Humans
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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 ...
Machine Learning Algorithms Neural Networks, Computer Humans Pattern Recognition, Automated Image Processing, Computer-Assisted
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Dual selective fusion transformer network for hyperspectral image classification.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Transformer has achieved satisfactory results in the field of hyperspectral image (HSI) classification. However, existing Transformer models face two key challenges when dealing with HSI scenes characterized by diverse land cover types and rich spect...
Algorithms Neural Networks, Computer Hyperspectral Imaging Image Processing, Computer-Assisted
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Episodic Memory-Double Actor-Critic Twin Delayed Deep Deterministic Policy Gradient.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Existing deep reinforcement learning (DRL) algorithms suffer from the problem of low sample efficiency. Episodic memory allows DRL algorithms to remember and use past experiences with high return, thereby improving sample efficiency. However, due to ...
Memory, Episodic Algorithms Reinforcement, Psychology Deep Learning Reward Humans
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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...
Humans Machine Learning Neural Networks, Computer Algorithms
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ABVS breast tumour segmentation via integrating CNN with dilated sampling self-attention and feature interaction Transformer.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Given the rapid increase in breast cancer incidence, the Automated Breast Volume Scanner (ABVS) is developed to screen breast tumours efficiently and accurately. However, reviewing ABVS images is a challenging task owing to the significant variations...
Neural Networks, Computer Algorithms Humans Imaging, Three-Dimensional Breast Neoplasms Image Processing, Computer-Assisted Female
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RISE-Editing: Rotation-invariant neural point fields with interactive segmentation for fine-grained and efficient editing.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Neural Radiance Fields (NeRF) have shown great potential for synthesizing novel views. Currently, despite the existence of some initial controllable and editable NeRF methods, they remain limited in terms of efficient and fine-grained editing capabil...
Rotation Algorithms Humans Neural Networks, Computer
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