AIMC Topic: Learning

Clear Filters Showing 1271 to 1280 of 1476 articles

Adaptive node-level weighted learning for directed graph neural network.

Neural networks : the official journal of the International Neural Network Society
Directed graph neural networks (DGNNs) have garnered increasing interest, yet few studies have focused on node-level representation in directed graphs. In this paper, we argue that different nodes rely on neighbor information from different direction...

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
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: ...

DuPt: Rehearsal-based continual learning with dual prompts.

Neural networks : the official journal of the International Neural Network Society
The rehearsal-based continual learning methods usually involve reviewing a small number of representative samples to enable the network to learn new contents while retaining old knowledge. However, existing works overlook two crucial factors: (1) Whi...

Exploiting instance-label dynamics through reciprocal anchored contrastive learning for few-shot relation extraction.

Neural networks : the official journal of the International Neural Network Society
In the domain of Few-shot Relation Extraction (FSRE), the primary objective is to distill relational facts from limited labeled datasets. This task has recently witnessed significant advancements through the integration of Pre-trained Language Models...

Memory flow-controlled knowledge tracing with three stages.

Neural networks : the official journal of the International Neural Network Society
Knowledge Tracing (KT), as a pivotal technology in intelligent education systems, analyzes students' learning data to infer their knowledge acquisition and predict their future performance. Recent advancements in KT recognize the importance of memory...

Heterogeneity, reinforcement learning, and chaos in population games.

Proceedings of the National Academy of Sciences of the United States of America
Inspired by the challenges at the intersection of Evolutionary Game Theory and Machine Learning, we investigate a class of discrete-time multiagent reinforcement learning (MARL) dynamics in population/nonatomic congestion games, where agents have div...

Constructing a predictive model of negative academic emotions in high school students based on machine learning methods.

Scientific reports
Negative academic emotions reflect the negative experiences that learners encounter during the learning process. This study aims to explore the effectiveness of machine learning algorithms in predicting high school students' negative academic emotion...

Exploring Generative Artificial Intelligence to Enhance Reflective Writing in Pharmacy Education.

American journal of pharmaceutical education
The integration of generative artificial intelligence (AI) holds the potential to impact teaching and learning. In this commentary, we explore the opportunity for AI to enhance reflective writing (RW) among student pharmacists. AI-guided RW has the p...

Humanoid interfaces in artificial intelligence-based language learning devices: Possible 'Uncanny Valley' effects?

Acta psychologica
The integration of artificial intelligence (AI) into educational tools is transforming learning environments by enabling personalized experiences. This study explores the effectiveness of AI-based educational interfaces, comparing humanoid avatar tut...

Continual Learning by Contrastive Learning of Regularized Classes in Multivariate Gaussian Distributions.

International journal of neural systems
Deep neural networks struggle with incremental updates due to catastrophic forgetting, where newly acquired knowledge interferes with the learned previously. Continual learning (CL) methods aim to overcome this limitation by effectively updating the ...