Jie Huang

Accelerated diffusion-based recommendation algorithm on tripartite graphs with GPU clusters

2016

Exorbitant computation cost hinders the practical application of recommendation algorithm, especially in time-critical application scenario. Although experiments show that recommendation algorithm based on an integrated diffusion on user-item-tag tripartite graphs can significantly improve accuracy, diversification …

Research on fast construction of question answering system based on target graph

2021

Aiming at the problems of chaotic structure and lack of visual query methods in small sample domain data, this paper proposes a fast construction framework of question answering (QA) system based on target graph. Firstly, …

Bayesian Bivariate Cure Rate Models Using Copula Functions

2022 · International Journal of Statistics and Probability

Bivariate survival cure rate models extend the understanding of time-to-event data by allowing for a cured fraction of the population and dependence between paired units and make more accurate and informative conclusions. In this paper, …

MetaASSIST: Robust Dialogue State Tracking with Meta Learning

2022

Existing dialogue datasets contain lots of noise in their state annotations. Such noise can hurt model training and ultimately lead to poor generalization performance. A general framework named ASSIST has recently been proposed to train …

A Named Entity Recognition Method Based on Knowledge Distillation and Efficient GlobalPointer for Chinese Medical Texts

2024 · IEEE Access

The task of named entity recognition has been widely used in medical text analysis, but there is still the problem of poor transfer ability in practical applications. This work proposes a novel named entity recognition …

Fed-SMAE: Federated-Learning Based Time Series Anomaly Detection with Shared Memory Augmented Autoencoder

2024

Time series anomaly detection plays a critical role in ensuring the security of Cyber-Physical Systems (CPS). However, the growing complexity of data acquired from CPS poses significant challenges to conventional anomaly detection methods. Deep learning-based …

Towards Reasoning in Large Language Models: A Survey

2023

Reasoning is a fundamental aspect of human intelligence that plays a crucial role in activities such as problem solving, decision making, and critical thinking. In recent years, large language models (LLMs) have made significant progress …