Search Results for author: Zimu Zheng

Found 3 papers, 1 papers with code

KubeEdge-Sedna v0.3: Towards Next-Generation Automatically Customized AI Engineering Scheme

no code implementations8 Mar 2023 Zimu Zheng

Edge-cloud collaborative lifelong learning adapts to data heterogeneity at different edge locations through (1) multi-task transfer learning to achieve accurate prediction of "thousands of people and thousands of faces"; (2) incremental processing of unknown tasks, the more systems learn and the smarter systems are with small samples, gradually realize AI engineering and automation; (3) Use the cloud-side knowledge base to remember new situational knowledge to avoid catastrophic forgetting; (4) The edge-cloud collaborative architecture enables data security compliance and edge AI services to be offline autonomy while applying cloud resources.

Transfer Learning

MLink: Linking Black-Box Models from Multiple Domains for Collaborative Inference

3 code implementations28 Sep 2022 Mu Yuan, Lan Zhang, Zimu Zheng, Yi-Nan Zhang, Xiang-Yang Li

The cost efficiency of model inference is critical to real-world machine learning (ML) applications, especially for delay-sensitive tasks and resource-limited devices.

Collaborative Inference Multi-Task Learning +1

On-edge Multi-task Transfer Learning: Model and Practice with Data-driven Task Allocation

no code implementations6 Jul 2021 Zimu Zheng, Qiong Chen, Chuang Hu, Dan Wang, Fangming Liu

We then show that task allocation with task importance for MTL (TATIM) is a variant of the NP-complete Knapsack problem, where the complicated computation to solve this problem needs to be conducted repeatedly under varying contexts.

Computational Efficiency Transfer Learning

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