no code implementations • 3 Feb 2024 • Zhuomin Chen, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian, Md Mezbahul Islam, Ananda Mohan Mondal, Hua Wei, Dongsheng Luo
A popular paradigm for the explainability of GNNs is to identify explainable subgraphs by comparing their labels with the ones of original graphs.
no code implementations • 20 Aug 2023 • Huiyuan Chen, Xiaoting Li, Vivian Lai, Chin-Chia Michael Yeh, Yujie Fan, Yan Zheng, Mahashweta Das, Hao Yang
In this paper, we present Sharpness-aware Collaborative Filtering (SharpCF), a simple yet effective method that conducts adversarial training without extra computational cost over the base optimizer.
no code implementations • 4 Jun 2023 • Xiaoting Li, Lingwei Chen, Dinghao Wu
To address this challenge, in this paper, we leverage the inherent vulnerability of machine learning to adversarial attacks, and design a novel text-space Adversarial attack for Social Good, called Adv4SG.
no code implementations • 8 Dec 2022 • Huiyuan Chen, Xiaoting Li, Kaixiong Zhou, Xia Hu, Chin-Chia Michael Yeh, Yan Zheng, Hao Yang
We found that our TinyKG with INT2 quantization aggressively reduces the memory footprint of activation maps with $7 \times$, only with $2\%$ loss in accuracy, allowing us to deploy KGNNs on memory-constrained devices.
no code implementations • 8 Dec 2022 • Huiyuan Chen, Yusan Lin, Menghai Pan, Lan Wang, Chin-Chia Michael Yeh, Xiaoting Li, Yan Zheng, Fei Wang, Hao Yang
Transformer-based sequential recommenders are very powerful for capturing both short-term and long-term sequential item dependencies.
no code implementations • 2 Dec 2022 • Xiaoting Li, Yuhang Wu, Vineeth Rakesh, Yusan Lin, Hao Yang, Fei Wang
Graph neural networks have achieved significant success in representation learning.
no code implementations • 17 Oct 2022 • Han Xu, Menghai Pan, Zhimeng Jiang, Huiyuan Chen, Xiaoting Li, Mahashweta Das, Hao Yang
The existence of adversarial attacks (or adversarial examples) brings huge concern about the machine learning (ML) model's safety issues.
no code implementations • 18 Sep 2020 • Le Xiao, Xiaoting Li, Datao Gong, Jinghong Chen, Di Guo, Huiqin He, Suen Hou, Guangming Huang, Chonghan Liu, Tiankuan Liu, Xiangming Sun, Ping-Kun Teng, Bozorgmehr Vosooghi, Annie C. Xiang, Jingbo Ye, Yang You, Zhiheng Zuo
In this paper, we present the design and test results of LOCx2, a transmitter ASIC for the ATLAS Liquid Argon Calorimeter trigger upgrade.
Instrumentation and Detectors