Name: Race
Type: User
Company: Northwestern University
Bio: I am now a third-year Computer Science Ph.D. student at Northwestern University.
Location: Evanston, IL, U.S.
Blog: https://sites.google.com/view/lixu-wang-homepage/homepage
Race's Projects
This is the code for Addressing Class Imbalance in Federated Learning (AAAI-2021).
This is the repository that introduces research topics related to protecting intellectual property (IP) of AI from a data-centric perspective. Such topics include data-centric model IP protection, data authorization protection, data copyright protection, and any other data-level technologies that protect the IP of AI.
This is the code implementation of the paper "Financial Trading as a Game: A Deep Reinforcement Learning Approach".
This is the formal code implementation of the CVPR 2022 paper 'Federated Class Incremental Learning'.
Federated Learning with New Knowledge -- explore to incorporate various new knowledge into existing FL systems and evolve these systems to reduce costs, extend their lifespan, and facilitate sustainable development.
This is the code of ICLR 2022 Oral paper 'Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization'.
Continual Model Generalization for Unseen Domains
This is the code for the final project of EE 332 in Northwestern.