Chenwei Wu

Secure Data Sharing With Flow Model

2020 · arXiv (Cornell University)

In the classical multi-party computation setting, multiple parties jointly compute a function without revealing their own input data. We consider a variant of this problem, where the input data can be shared for machine learning …

Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup

2022 · arXiv (Cornell University)

Mixup is a data augmentation technique that relies on training using random convex combinations of data points and their labels. In recent years, Mixup has become a standard primitive used in the training of state-of-the-art …

Multimodal Deep Learning for Low-Resource Settings: A Vector Embedding Alignment Approach for Healthcare Applications

2024 · medRxiv

Abstract Objective Large-scale multi-modal deep learning models and datasets have revolutionized various domains such as healthcare, underscoring the critical role of computational power. However, in resource-constrained regions like Low and Middle-Income Countries (LMICs), GPU and …