A Joint Model and Data Driven Method for Distributed Estimation

no code implementations • 30 Mar 2023 • Meng He, Ran Li, Chuan Huang, Shulong Zhang

To this end, we propose a joint model and data driven distributed estimation method by designing the optimal quantizers and fusion center (FC) based on the Bayesian and minimum mean square error (MMSE) criterions.

Quantization Weather Forecasting

R2F: A Remote Retraining Framework for AIoT Processors with Computing Errors

no code implementations • 7 Jul 2021 • Dawen Xu, Meng He, Cheng Liu, Ying Wang, Long Cheng, Huawei Li, Xiaowei Li, Kwang-Ting Cheng

It takes the remote AIoT processor with soft errors in the training loop such that the on-site computing errors can be learned with the application data on the server and the retrained models can be resilient to the soft errors.

Distance Oracles for Interval Graphs via Breadth-First Rank/Select in Succinct Trees

no code implementations • 15 May 2020 • Meng He, J. Ian Munro, Yakov Nekrich, Sebastian Wild, Kaiyu Wu

We present the first succinct distance oracles for (unweighted) interval graphs and related classes of graphs, using a novel succinct data structure for ordinal trees that supports the mapping between preorder (i. e., depth-first) ranks and level-order (breadth-first) ranks of nodes in constant time.

Data Structures and Algorithms