Federated learning (FL) has emerged as a powerful paradigm for learning from decentralized data, and federated domain generalization further considers the test dataset (target domain) is absent from the decentralized training data (source domains).
Fine-tuning the learnable prompt for a pre-trained vision-language model (VLM), such as CLIP, has demonstrated exceptional efficiency in adapting to a broad range of downstream tasks. Existing prompt tuning methods for VLMs do not distinguish spurious features introduced by biased training data from invariant features, and employ a uniform alignment process when adapting to unseen target domains.
Our research focuses on the software and hardware synergy of on-device learning techniques, covering the scope of model-level neural network design, algorithm-level training optimization and hardware-level arithmetic acceleration.
Our research focuses on the software and hardware synergy of on-device learning techniques, covering the scope of model-level neural network design, algorithm-level training optimization and hardware-level arithmetic acceleration.
Our team aims at the next-generation blockchain system with scalability, security, privacy, and intelligence and our proposed architecture is composed of 6 layers as above. In the following, the details of these 6 layers will be explained from top to bottom.
To tackle non-IID data challenge in FL, we consider to design a new method to improve training efficiency of each client from the perspective of whole training process.
Blockchain-empowered edge learning is a novel distributed learning architecture to dispense with a dedicated server in traditional distributed learning and provide trustworthy training for edge devices.
Payment channel network (PCN) is the most promising off-chain technologies to support massive micro payments for blockchain. The technology has been deployed in a number of blockchains including Bitcoin and Ethereum.
Personal data produced from widely emerged cyberspace activities are expected to promote information dissemination and engagement, or even make business intelligence more powerful.