1 code implementation • 29 May 2024 • Jiajie Li, Bo Gu, Shimin Gong, Zhou Su, Mohsen Guizani
Given sensing data submitted by MUs, PRBTD can eliminate the data with heavy noise and identify malicious MUs with high accuracy.
no code implementations • 12 Mar 2024 • Jiajie Li, JinJun Xiong
However, the use of non-linear activations such as ReLU in DNNs can lead to impractically high PI latency in existing PI systems, as ReLU requires the use of costly MPC computations, such as Garbled Circuits.
no code implementations • 25 Oct 2023 • Kejiang Qian, Lingjun Mao, Xin Liang, Yimin Ding, Jin Gao, Xinran Wei, Ziyi Guo, Jiajie Li
By integrating Multi-Agent Reinforcement Learning, our framework ensures that participatory urban planning decisions are more dynamic and adaptive to evolving community needs and provides a robust platform for automating complex real-world urban planning processes.
no code implementations • 17 Jun 2023 • Jiajie Li, Jian Wang, Chen Wang, JinJun Xiong
In this paper, we present a novel approach for image harmonization by leveraging diffusion models.
no code implementations • 18 Apr 2023 • Yuanwei Fang, Zihao Liu, Yanheng Lu, Jiawei Liu, Jiajie Li, Yi Jin, Jian Chen, Yenkuang Chen, Hongzhong Zheng, Yuan Xie
Furthermore, NPS shows higher accuracy and generality than the state-of-the-art GNN approach in code behavior learning, enabling the generation of high-quality execution embeddings.
no code implementations • ICCV 2023 • Yuhong Li, Jiajie Li, Cong Hao, Pan Li, JinJun Xiong, Deming Chen
We further propose a Discrete Proxy Search (DPS) method to find the optimized training settings for Eproxy with only a handful of benchmarked architectures on the target tasks.
1 code implementation • 17 Oct 2022 • Yuhong Li, Jiajie Li, Cong Han, Pan Li, JinJun Xiong, Deming Chen
(2) Efficient proxies are not extensible to multi-modality downstream tasks.
no code implementations • 25 Jul 2022 • Yuwei Hu, Jiajie Li, Zhongming Yu, Zhiru Zhang
To understand whether persistent memory is a good fit for GNNRecSys training, we perform an in-depth characterization of GNNRecSys workloads and a comprehensive analysis of their performance on a persistent memory device, namely, Intel Optane.