This project explores domain adaptation & online learning for model customization considering privacy preservation and secure communication. We propose blockchain-based peer-to-peer federated learning (P2PDL) using federated learning applications.
We propose the ModelKB system automating end-to-end model management in deep learning. We will develop a ModelKB prototype that can automatically (1) extract and store the model’s metadata-including its architecture, weights, and configuration; (2) visualize, query, and compare experiments; and (3) reproduce experiments.
DeepCloud is designed as an open software-defined ecosystem for researchers at different levels with the following salient features and transformative impacts. It is one of the first massively scalable multi-tenant open cloud platform with full-fledged building blocks and comprehensive shared stores (app, model, knowledge, data) for deep learning research and applications.
Provide Realtime live 3D map service from mobile edge using distributed sensing and low latency point cloud aggregation and multicasting. We will use high efficiency scalable point cloud source coding. We will provide real time point cloud LiveMaps aggregated through mobile edge computing. We propose a joint source-channel coding for V2V and V2I communication.