Neural networks : the official journal of the International Neural Network Society
Mar 12, 2025
This paper proposes a novel one-layer neural network to solve quadratic programming problems in real time by using a control parameter and transforming the optimality conditions into a system of projection equations. The proposed network includes two...
Neural networks : the official journal of the International Neural Network Society
Mar 12, 2025
Large Language Models (LLMs), which are trained on massive text data, have demonstrated remarkable advancements in language understanding capabilities. Nevertheless, it remains unclear to what extent LLMs have effectively captured and utilized the im...
Neural networks : the official journal of the International Neural Network Society
Mar 12, 2025
Federated learning (FL) enables collaborative model training without direct data sharing, facilitating knowledge exchange while ensuring data privacy. Multimodal federated learning (MFL) is particularly advantageous for decentralized multimodal data,...
Neural networks : the official journal of the International Neural Network Society
Mar 11, 2025
In the context of few-shot classification, the goal is to train a classifier using a limited number of samples while maintaining satisfactory performance. However, traditional metric-based methods exhibit certain limitations in achieving this objecti...
Neural networks : the official journal of the International Neural Network Society
Mar 11, 2025
The exploration-exploitation dilemma is one of the fundamental challenges in deep reinforcement learning (RL). Agents must strike a trade-off between making decisions based on current beliefs or gathering more information. Prior work mostly prefers d...
Neural networks : the official journal of the International Neural Network Society
Mar 11, 2025
Graph Neural Networks (GNNs) have gained considerable prominence in semi-supervised learning tasks in processing graph-structured data, primarily owing to their message-passing mechanism, which largely relies on the availability of clean labels. Howe...
Neural networks : the official journal of the International Neural Network Society
Mar 10, 2025
Semi-supervised learning can significantly boost model performance by leveraging unlabeled data, particularly when labeled data is scarce. However, real-world unlabeled data often contain unseen-class samples, which can hinder the classification of s...
Neural networks : the official journal of the International Neural Network Society
Mar 10, 2025
High-voltage defibrillation for eliminating cardiac spiral waves has significant side effects, necessitating the pursuit of low-energy alternatives for a long time. Adaptive optimization techniques and machine learning methods provide promising solut...
Neural networks : the official journal of the International Neural Network Society
Mar 10, 2025
In real-world scenarios, multi-view multi-label learning often encounters the challenge of incomplete training data due to limitations in data collection and unreliable annotation processes. The absence of multi-view features impairs the comprehensiv...
Neural networks : the official journal of the International Neural Network Society
Mar 10, 2025
Deep learning for Electroencephalography (EEG) has become dominant in the tasks of discrimination and evaluation of brain disorders. However, despite its significant successes, this approach has long been facing challenges due to the limited availabi...