Researchers propose a self-distillation fix for ‘catastrophic forgetting’ in LLMs

LLMs tend to lose prior skills when fine-tuned for new tasks. A new self-distillation approach aims to reduce regression and ...
IEEE

Intelligent Movie Recommendation Platform with AI-Driven Recommendation using Machine Learning with Optimized Power Saving Methods

Abstract: The movie recommendation system utilises an AI-powered method that improves collaborative filtering by employing the K-Nearest Neighbours (K-NN) algorithm. This system provides personalised ...

Sophelio Launches Data Fusion Labeler (dFL) to Accelerate Sensor Data Preparation for Machine Learning

Sophelio Introduces the Data Fusion Labeler (dFL) for Multimodal Time-Series Data - The only labeling and harmonization ...
SciELO

Machine learning for high-risk hospitalization prediction in outpatient individuals with diabetes at a tertiary hospital

Objective: To characterize, via a predictive model using real-world data, patients with diabetes with a heightened probability of hospitalization. Methods: At the Endocrinology Unit of a tertiary ...
BMJ

Machine learning methods, applications and economic analysis to predict heart failure hospitalisation risk: a scoping review

Background Machine Learning (ML) has been transformative in healthcare, enabling more precise diagnostics, personalised treatment regimens and enhanced patient care. In cardiology, ML plays a crucial ...
IEEE

RADAR: Reliable Aligned Decoding and Resampling for Semi-Supervised Node Classification with Graph Contrastive Learning

Abstract: Graph contrastive learning (GCL) leverages semantic consistency as contrastive signals and has shown strong performance in semi-supervised node classification. However, real-world graphs ...