5 papers
Mpemba Effect in Large-Language Model Training Dynamics: A Minimal Analysis of the Valley-River model
Sibei Liu, Zhijian Hu
Learning rate (LR) schedules in large language model (LLM) training often follow empirical templates: warm-up, constant plateau/stable phase, and decay (WSD). However, the mechanis…
Gated Multimodal Graph Learning for Personalized Recommendation
Sibei Liu, Yuanzhe Zhang, Xiang Li +3
Multimodal recommendation has emerged as a promising solution to alleviate the cold-start and sparsity problems in collaborative filtering by incorporating rich content information…
User Behavior Analysis in Privacy Protection with Large Language Models: A Study on Privacy Preferences with Limited Data
Haowei Yang, Qingyi Lu, Yang Wang +3
With the widespread application of large language models (LLMs), user privacy protection has become a significant research topic. Existing privacy preference modeling methods often…
Optimization and Application of Cloud-based Deep Learning Architecture for Multi-Source Data Prediction
Yang Zhang, Fa Wang, Xin Huang +3
This study develops a cloud-based deep learning system for early prediction of diabetes, leveraging the distributed computing capabilities of the AWS cloud platform and deep learni…
Predicting 30-Day Hospital Readmission in Medicare Patients: Insights from an LSTM Deep Learning Model
Xintao Li, Sibei Liu, Dezhi Yu +2
Readmissions among Medicare beneficiaries are a major problem for the US healthcare system from a perspective of both healthcare operations and patient caregiving outcomes. Our stu…