1 code implementation • 10 May 2024 • Zhiyuan Ning, Chunlin Tian, Meng Xiao, Wei Fan, Pengyang Wang, Li Li, Pengfei Wang, Yuanchun Zhou
Federated Learning faces significant challenges in statistical and system heterogeneity, along with high energy consumption, necessitating efficient client selection strategies.
2 code implementations • 9 Apr 2024 • Ping Xu, Zhiyuan Ning, Meng Xiao, Guihai Feng, Xin Li, Yuanchun Zhou, Pengfei Wang
Addressing these limitations, we introduce scCDCG (single-cell RNA-seq Clustering via Deep Cut-informed Graph), a novel framework designed for efficient and accurate clustering of scRNA-seq data that simultaneously utilizes intercellular high-order structural information.
no code implementations • 5 Mar 2024 • Mengyi Huang, Meng Xiao, Ludi Wang, Yi Du
Continuous Relation Extraction (CRE) aims to incrementally learn relation knowledge from a non-stationary stream of data.
no code implementations • 18 Feb 2024 • Cong Li, Meng Xiao, Pengfei Wang, Guihai Feng, Xin Li, Yuanchun Zhou
Despite the inherent limitations of existing Large Language Models in directly reading and interpreting single-cell omics data, they demonstrate significant potential and flexibility as the Foundation Model.
no code implementations • 9 Oct 2023 • Xunxin Cai, Meng Xiao, Zhiyuan Ning, Yuanchun Zhou
In addressing the imbalanced issue of data within the realm of Natural Language Processing, text data augmentation methods have emerged as pivotal solutions.
no code implementations • 19 Sep 2023 • Ziyue Qiao, Xiao Luo, Meng Xiao, Hao Dong, Yuanchun Zhou, Hui Xiong
To deal with the domain shift, we add adaptive shift parameters to each of the source nodes, which are trained in an adversarial manner to align the cross-domain distributions of node embedding, thus the node classifier trained on labeled source nodes can be transferred to the target nodes.
no code implementations • 6 Sep 2023 • Hao Dong, Pengyang Wang, Meng Xiao, Zhiyuan Ning, Pengfei Wang, Yuanchun Zhou
Subsequently, we utilize the defined query-aware temporal paths on a history temporal graph to model historical path information related to queries for reasoning.
no code implementations • 4 Sep 2023 • Meng Xiao, Min Wu, Ziyue Qiao, Yanjie Fu, Zhiyuan Ning, Yi Du, Yuanchun Zhou
The objective of topic inference in research proposals aims to obtain the most suitable disciplinary division from the discipline system defined by a funding agency.
1 code implementation • 29 Jun 2023 • Meng Xiao, Dongjie Wang, Min Wu, Kunpeng Liu, Hui Xiong, Yuanchun Zhou, Yanjie Fu
Feature transformation aims to reconstruct an effective representation space by mathematically refining the existing features.
no code implementations • 26 Feb 2023 • Meng Xiao, Dongjie Wang, Min Wu, Pengfei Wang, Yuanchun Zhou, Yanjie Fu
Furthermore, we reconstruct feature selection solutions using these embeddings and select the feature subset with the highest performance for downstream tasks as the optimal subset.
1 code implementation • 27 Dec 2022 • Meng Xiao, Dongjie Wang, Min Wu, Ziyue Qiao, Pengfei Wang, Kunpeng Liu, Yuanchun Zhou, Yanjie Fu
Feature transformation for AI is an essential task to boost the effectiveness and interpretability of machine learning (ML).
1 code implementation • 27 Dec 2022 • Xu Ye, Meng Xiao, Zhiyuan Ning, Weiwei Dai, Wenjuan Cui, Yi Du, Yuanchun Zhou
It aims to evaluate the condition of both eyes of a patient respectively, and we formulate it as a particular multi-label classification task in this paper.
no code implementations • 28 Sep 2022 • Meng Xiao, Min Wu, Ziyue Qiao, Zhiyuan Ning, Yi Du, Yanjie Fu, Yuanchun Zhou
In response to this question, we propose a hierarchical mixup multiple-label classification framework, which we called H-MixUp.
no code implementations • 16 Sep 2022 • Meng Xiao, Ziyue Qiao, Yanjie Fu, Hao Dong, Yi Du, Pengyang Wang, Hui Xiong, Yuanchun Zhou
Specifically, we first propose a hierarchical transformer to extract the textual semantic information of proposals.
no code implementations • 16 Sep 2022 • Meng Xiao, Dongjie Wang, Min Wu, Kunpeng Liu, Hui Xiong, Yuanchun Zhou, Yanjie Fu
Feature transformation aims to extract a good representation (feature) space by mathematically transforming existing features.
1 code implementation • 22 Jul 2022 • Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, Guchun Zhang, Yinpeng Guo, Zhongqi Li, Qi Zhang, Meng Xiao, Bo Shen, Lin Li, Hao Yu, Li Yan, Pingyi Zhou, Xin Wang, Yuchi Ma, Ignacio Iacobacci, Yasheng Wang, Guangtai Liang, Jiansheng Wei, Xin Jiang, Qianxiang Wang, Qun Liu
We present PanGu-Coder, a pretrained decoder-only language model adopting the PanGu-Alpha architecture for text-to-code generation, i. e. the synthesis of programming language solutions given a natural language problem description.
no code implementations • 7 Mar 2022 • Meng Xiao, Ziyue Qiao, Yanjie Fu, Hao Dong, Yi Du, Pengyang Wang, Dong Li, Yuanchun Zhou
After extracting the semantic and interdisciplinary knowledge, we design a level-wise prediction component to fuse the two types of knowledge representations and detect interdisciplinary topic paths for each proposal.
1 code implementation • 8 Oct 2021 • Ziyue Qiao, Yanjie Fu, Pengyang Wang, Meng Xiao, Zhiyuan Ning, Denghui Zhang, Yi Du, Yuanchun Zhou
In this paper, we propose a multi-task self-supervised learning-based researcher data pre-training model named RPT.
no code implementations • 14 Sep 2021 • Meng Xiao, Ziyue Qiao, Yanjie Fu, Yi Du, Pengyang Wang
In this paper, we formulate the proposal classification problem into a hierarchical multi-label classification task.