no code implementations • ISA (LREC) 2022 • Min Dong, Xiaoyan Liu, Alex Chengyu Fang
SFL seeks to explain identifiable, observable phenomena of language use in context through the application of a theoretical framework which models language as a functional, meaning making system (Halliday & Matthiessen 2004).
no code implementations • 21 Mar 2024 • Yong He, Hongshan Yu, Muhammad Ibrahim, Xiaoyan Liu, Tongjia Chen, Anwaar Ulhaq, Ajmal Mian
This strategy allows various transformer blocks to share the same position information over the same resolution points, thereby reducing network parameters and training time without compromising accuracy. Experimental comparisons with existing methods on multiple datasets demonstrate the efficacy of SMTransformer and skip-attention-based up-sampling for point cloud processing tasks, including semantic segmentation and classification.
1 code implementation • 29 Oct 2023 • Hao Zhang, Yang Liu, Xiaoyan Liu, Tianming Liang, Gaurav Sharma, Liang Xue, Maozu Guo
We introduce a novel graph-based framework for alleviating key challenges in distantly-supervised relation extraction and demonstrate its effectiveness in the challenging and important domain of biomedical data.
no code implementations • 8 Mar 2023 • Yong He, Hongshan Yu, Zhengeng Yang, Xiaoyan Liu, Wei Sun, Ajmal Mian
In particular, we achieve state-of-the-art semantic segmentation results of 76% mIoU on S3DIS 6-fold and 72. 2% on S3DIS Area5.
no code implementations • 22 Sep 2022 • Xiaoyan Liu, Zehui Dong, Zhiwei Xu, Siyuan Liu, Jie Tian
Federated learning (FL) is emerging as a new paradigm to train machine learning (ML) models in distributed systems, including vehicles in V2X networks.
no code implementations • 2 Dec 2021 • Xiaoyan Liu, Zhiwei Xu, Yana Qin, Jie Tian
New intelligence applications are driving increasing interest in deploying deep neural networks (DNN) in a distributed way.
1 code implementation • 24 May 2021 • Tianming Liang, Yang Liu, Xiaoyan Liu, Hao Zhang, Gaurav Sharma, Maozu Guo
On top of that, we further propose a novel constraint graph-based relation extraction framework(CGRE) to handle the two challenges simultaneously.
no code implementations • 9 Mar 2021 • Yong He, Hongshan Yu, Xiaoyan Liu, Zhengeng Yang, Wei Sun, Ajmal Mian
This paper fills the gap and provides a comprehensive survey of the recent progress made in deep learning based 3D segmentation.
1 code implementation • 11 Nov 2020 • Lucas Rosenblatt, Xiaoyan Liu, Samira Pouyanfar, Eduardo de Leon, Anuj Desai, Joshua Allen
Differentially private data synthesis protects personal details from exposure, and allows for the training of differentially private machine learning models on privately generated datasets.
1 code implementation • 6 Feb 2020 • Mingzhen Li, Yi Liu, Xiaoyan Liu, Qingxiao Sun, Xin You, Hailong Yang, Zhongzhi Luan, Lin Gan, Guangwen Yang, Depei Qian
In this paper, we perform a comprehensive survey of existing DL compilers by dissecting the commonly adopted design in details, with emphasis on the DL oriented multi-level IRs, and frontend/backend optimizations.