Li Chen

Robust Vertex Classification

2015 · IEEE Transactions on Pattern Analysis and Machine Intelligence

For random graphs distributed according to stochastic blockmodels, a special case of latent position graphs, adjacency spectral embedding followed by appropriate vertex classification is asymptotically Bayes optimal; but this approach requires knowledge of and critically …

Breast Cancer Diagnosis from Perspective of Class Imbalance

2019 · DOAJ (DOAJ: Directory of Open Access Journals)

Introduction: Breast cancer is the second cause of mortality among women. Early detection is the only rescue to reduce the risk of breast cancer mortality. Traditional methods cannot effectively diagnose tumor since they are based …

Toward Automated Calibration of Data Center Digital Twins: A Neural Surrogate Approach

2020 · arXiv (Cornell University)

Evolving the computational fluid dynamics (CFD) model to high fidelity digital twin is desirable for industrial data center management. However, existing CFD model calibration approaches to improve the model accuracy require either excessive manual tuning …

BU-Trace: A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing

2021 · arXiv (Cornell University)

The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented health crisis for the global. Digital contact tracing, as a transmission intervention measure, has shown its effectiveness on pandemic control. Despite intensive research on digital …

Research on Unit Knowledge Structure Teaching from the Perspective of Advanced Learning

2022 · Contemporary Education and Teaching Research

Based on the knowledge structure of integrated units, it emphasizes that every knowledge point should be put into the complete unit knowledge structure to understand, so that learners can be promoted from the previous structure …

Can Deep Learning Do Everything in AI? An Exploration of Simple Examples in Image Segmentation

2024

Nowadays, Deep Learning, especially ChatGPT and other Generative AI-related products provides tremendous opportunities as tools for so many tasks and jobs, from science to engineering to education. However, when the author asked for programming code …

RankGraph: Unified Heterogeneous Graph Learning for Cross-Domain Recommendation

2025 · arXiv (Cornell University)

Cross-domain recommendation systems face the challenge of integrating fine-grained user and item relationships across various product domains. To address this, we introduce RankGraph, a scalable graph learning framework designed to serve as a core component …

Explaining Recommendations Based on Feature Sentiments in Product Reviews

2017

The explanation interface has been recognized important in recommender systems as it can help users evaluate recommendations in a more informed way for deciding which ones are relevant to their interests. In different decision environments, …

A Survey on Conversational Recommender Systems

2021 · ACM Computing Surveys

Recommender systems are software applications that help users to find items of interest in situations of information overload. Current research often assumes a one-shot interaction paradigm, where the users’ preferences are estimated based on past …

Generate Neural Template Explanations for Recommendation

2020

Personalized recommender systems are important to assist user decision-making in the era of information overload. Meanwhile, explanations of the recommendations further help users to better understand the recommended items so as to make informed choices, …