Jin Chen

Ensemble: A Tool for Performance Modeling of Applications in Cloud Data Centers

2015 · IEEE Transactions on Cloud Computing

We introduce Ensemble, a runtime framework and associated tools for building application performance models on-the-fly. These dynamic performance models can be used to support complex, highly dimensional resource allocation, and/or what-if performance inquiry in modern …

Domain Adversarial Reinforcement Learning for Partial Domain Adaptation

2019 · arXiv (Cornell University)

Partial domain adaptation aims to transfer knowledge from a label-rich source domain to a label-scarce target domain which relaxes the fully shared label space assumption across different domains. In this more general and practical scenario, …

KIT-LSTM: Knowledge-guided Time-aware LSTM for Continuous Clinical Risk Prediction

2022 · medRxiv

Abstract Rapid accumulation of temporal Electronic Health Record (EHR) data and recent advances in deep learning have shown high potential in precisely and timely predicting patients’ risks using AI. However, most existing risk prediction approaches …

Spatial interrelation matters: advancing 3D mineral prospectivity modeling with fully-connected CRFs—insights from Sanshandao Gold Belt, Eastern China

2025 · Ore Geology Reviews

The data-driven Three-Dimensional Mineral Prospectivity Modeling (3D MPM) has become an essential tool for localizing and quantifying concealed mineral resources. Machine learning techniques have become a cornerstone of 3D MPM, enabling the mapping of spatial …

Squeeze Out Tokens from Sample for Finer-Grained Data Governance

2025 · arXiv (Cornell University)

Widely observed data scaling laws, in which error falls off as a power of the training size, demonstrate the diminishing returns of unselective data expansion. Hence, data governance is proposed to downsize datasets through pruning …