6 papers
Class-aware Latent Attention Replay (CLAR): Class Incremental Hazard Diagnosis for Resilient AI in the Manufacturing Industrial Internet
Avranshu Mahanty, Ran Jin, Yingyan Zeng
Artificial Intelligence (AI) systems provide critical computation services in the Manufacturing Industrial Internet (MII), and their resilience depends on timely diagnosis of hazar…
Beyond Euclidean Summaries: Online Change Point Detection for Distribution-Valued Data
Yingyan Zeng, Yujing Huang, Xiaoyu Chen
Existing online change-point detection (CPD) methods rely on fixed-dimensional Euclidean summaries, implicitly assuming that distributional changes are well captured by moment-base…
Hierarchical Dataset Selection for High-Quality Data Sharing
Xiaona Zhou, Yingyan Zeng, Ran Jin +1
The success of modern machine learning hinges on access to high-quality training data. In many real-world scenarios, such as acquiring data from public repositories or sharing acro…
FAIR: Facilitating Artificial Intelligence Resilience in Manufacturing Industrial Internet
Yingyan Zeng, Ismini Lourentzou, Xinwei Deng +1
Artificial intelligence (AI) systems have been increasingly adopted in the Manufacturing Industrial Internet (MII). Investigating and enabling the AI resilience is very important t…
Ensemble Active Learning by Contextual Bandits for AI Incubation in Manufacturing
Yingyan Zeng, Xiaoyu Chen, Ran Jin
It is challenging but important to save annotation efforts in streaming data acquisition to maintain data quality for supervised learning base learners. We propose an ensemble acti…
ModelPred: A Framework for Predicting Trained Model from Training Data
Yingyan Zeng, Jiachen T. Wang, Si Chen +3
In this work, we propose ModelPred, a framework that helps to understand the impact of changes in training data on a trained model. This is critical for building trust in various s…