5 papers
Can Generative Artificial Intelligence Survive Data Contamination? Theoretical Guarantees under Contaminated Recursive Training
Kevin Wang, Hongqian Niu, Didong Li
As artificial intelligence (AI)-generated content proliferates, models are increasingly trained on their own outputs, risking progressive degradation or collapse. In this article,…
Understanding Overparametrization in Survival Models through Interpolation
Yin Liu, Jianwen Cai, Didong Li
Classical statistical learning theory predicts a U-shaped relationship between test loss and model capacity, driven by the bias-variance trade-off. Recent advances in modern machin…
An Operational Deep Learning System for Satellite-Based High-Resolution Global Nowcasting
Shreya Agrawal, Mohammed Alewi Hassen, Emmanuel Asiedu Brempong +16
Precipitation nowcasting, which predicts rainfall up to a few hours ahead, is a critical tool for vulnerable communities in the Global South frequently exposed to intense, rapidly…
Lower Ricci Curvature for Hypergraphs
Shiyi Yang, Can Chen, Didong Li
Networks with higher-order interactions, prevalent in biological, social, and information systems, are naturally represented as hypergraphs, yet their structural complexity poses f…
Applying Deep Learning to Ads Conversion Prediction in Last Mile Delivery Marketplace
Di Li, Xiaochang Miao, Huiyu Song +3
Deep neural networks (DNNs) have revolutionized web-scale ranking systems, enabling breakthroughs in capturing complex user behaviors and driving performance gains. At DoorDash, we…