no code implementations • 21 Nov 2023 • Shufa Wei, Xiaolong Xu, Xianbiao Qi, Xi Yin, Jun Xia, Jingyi Ren, Peijun Tang, Yuxiang Zhong, Yihao Chen, Xiaoqin Ren, Yuxin Liang, Liankai Huang, Kai Xie, Weikang Gui, Wei Tan, Shuanglong Sun, Yongquan Hu, Qinxian Liu, Nanjin Li, Chihao Dai, Lihua Wang, Xiaohui Liu, Lei Zhang, Yutao Xie
Our training corpus mainly consists of academic papers, thesis, content from some academic domain, high-quality Chinese data and others.
no code implementations • 31 Oct 2023 • Ruofan Wu, Mingyang Zhang, Lingjuan Lyu, Xiaolong Xu, Xiuquan Hao, Xinyi Fu, Tengfei Liu, Tianyi Zhang, Weiqiang Wang
The paradigm of vertical federated learning (VFL), where institutions collaboratively train machine learning models via combining each other's local feature or label information, has achieved great success in applications to financial risk management (FRM).
no code implementations • 5 Jul 2023 • Yiyao Zhou, Qianggang Wang, Yuan Chi, Jianquan Liao, Tao Huang, Niancheng Zhou, Xiaolong Xu, Xuefei Zhang
Optimal power flow (OPF) is a fundamental tool for analyzing the characteristics of bipolar DC distribution network (DCDN).
1 code implementation • 22 Jun 2023 • Haolong Xiang, Xuyun Zhang, Hongsheng Hu, Lianyong Qi, Wanchun Dou, Mark Dras, Amin Beheshti, Xiaolong Xu
Extensive experiments on a series of benchmarking datasets for comparative and ablation studies demonstrate that our approach can efficiently and robustly achieve better detection performance in general than the state-of-the-arts including the deep learning based methods.
1 code implementation • 23 May 2023 • Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen
Anomaly detection aims to distinguish abnormal instances that deviate significantly from the majority of benign ones.
1 code implementation • 2 May 2023 • Jianquan Li, Xidong Wang, Xiangbo Wu, Zhiyi Zhang, Xiaolong Xu, Jie Fu, Prayag Tiwari, Xiang Wan, Benyou Wang
Moreover, we also experimentally show the benefit of the proposed dataset in many aspects: (i) trained models for other QA datasets in a zero-shot fashion; and (ii) as external knowledge for retrieval-augmented generation (RAG); and (iii) improving existing pre-trained language models by using the QA pairs as a pre-training corpus in continued training manner.
no code implementations • 20 Feb 2023 • Qi Liu, ZhiYun Yang, Ru Ji, Yonghong Zhang, Muhammad Bilal, Xiaodong Liu, S Vimal, Xiaolong Xu
Radars are widely used to obtain echo information for effective prediction, such as precipitation nowcasting.
no code implementations • 27 Jan 2023 • Xiaolong Xu, Lingjuan Lyu, Yihong Dong, Yicheng Lu, Weiqiang Wang, Hong Jin
With the frequent happening of privacy leakage and the enactment of privacy laws across different countries, data owners are reluctant to directly share their raw data and labels with any other party.
no code implementations • 1 Dec 2022 • Tianyu Xia, Shuheng Shen, Su Yao, Xinyi Fu, Ke Xu, Xiaolong Xu, Xing Fu
As one way to implement privacy-preserving AI, differentially private learning is a framework that enables AI models to use differential privacy (DP).
2 code implementations • 25 Aug 2021 • Wei Shen, Chuheng Zhang, Yun Tian, Liang Zeng, Xiaonan He, Wanchun Dou, Xiaolong Xu
However, without node content (i. e., side information) for training, the user (or item) specific representation can not be learned in the inductive setting, that is, a model trained on one group of users (or items) cannot adapt to new users (or items).
Ranked #3 on Recommendation Systems on MovieLens 1M
no code implementations • 22 Jun 2021 • Xiang Ni, Xiaolong Xu, Lingjuan Lyu, Changhua Meng, Weiqiang Wang
Recently, Graph Neural Network (GNN) has achieved remarkable success in various real-world problems on graph data.
1 code implementation • 12 Jun 2020 • Shiqi Yang, Xiaolong Xu, Yaozheng Zhu, Ruirui Niu, Chunqiang Xu, Yuxuan Peng, Xing Cheng, Xionghui Jia, Xiaofeng Xu, Jianming Lu, Yu Ye
However, the layer-dependent magnetism of MnBi2Te4, which is fundamental and crucial for further exploration of quantum phenomena in this system, remains elusive.
Materials Science
no code implementations • 14 Oct 2019 • Yuwei Yang, Fanman Meng, Hongliang Li, Qingbo Wu, Xiaolong Xu, Shuai Chen
The result by the matrix transformation can be regarded as an attention map with high-level semantic cues, based on which a transformation module can be built simply. The proposed transformation module is a general module that can be used to replace the transformation module in the existing few-shot segmentation frameworks.
Ranked #79 on Few-Shot Semantic Segmentation on PASCAL-5i (5-Shot)