no code implementations • EMNLP 2021 • Zheng Fang, Yanan Cao, Tai Li, Ruipeng Jia, Fang Fang, Yanmin Shang, Yuhai Lu
To alleviate label scarcity in Named Entity Recognition (NER) task, distantly supervised NER methods are widely applied to automatically label data and identify entities.
no code implementations • EMNLP 2020 • Ruipeng Jia, Yanan Cao, Hengzhu Tang, Fang Fang, Cong Cao, Shi Wang
Sentence-level extractive text summarization is substantially a node classification task of network mining, adhering to the informative components and concise representations.
Ranked #1 on Extractive Text Summarization on CNN / Daily Mail
no code implementations • COLING 2022 • Yubing Ren, Yanan Cao, Fang Fang, Ping Guo, Zheng Lin, Wei Ma, Yi Liu
Transforming the large amounts of unstructured text on the Internet into structured event knowledge is a critical, yet unsolved goal of NLP, especially when addressing document-level text.
no code implementations • 21 Nov 2023 • Gijs Mast, Xiaoyu Shen, Fang Fang
This paper introduces a novel approach for computing netting--set level and counterparty level exposures, such as Potential Future Exposure (PFE) and Expected Exposure (EE), along with associated sensitivities.
no code implementations • 3 Nov 2023 • Bibo Wu, Fang Fang, Xianbin Wang, Donghong Cai, Shu Fu, Zhiguo Ding
Subsequently, given the fuzzy based client-edge association, a joint edge server scheduling and resource allocation problem is formulated.
1 code implementation • 26 Oct 2023 • Shan Lu, Zhicheng Dong, Donghong Cai, Fang Fang, Dongcai Zhao
To avoid the local optimal solution of loss function and the model collapse, we introduce an exponential information measure into the loss function of GAN.
1 code implementation • 27 May 2023 • Yi Liu, Yuan Tian, Jianxun Lian, Xinlong Wang, Yanan Cao, Fang Fang, Wen Zhang, Haizhen Huang, Denvy Deng, Qi Zhang
Aiming at learning entity representations that can match divergent mentions, this paper proposes a Multi-View Enhanced Distillation (MVD) framework, which can effectively transfer knowledge of multiple fine-grained and mention-relevant parts within entities from cross-encoders to dual-encoders.
no code implementations • 18 Apr 2023 • Bibo Wu, Fang Fang, Xianbin Wang
To address these challenges, in this paper, a joint optimization problem of client selection and resource allocation is formulated, aiming to minimize the total time consumption of each round in FL over a non-orthogonal multiple access (NOMA) enabled wireless network.
no code implementations • 24 Feb 2023 • Yonghao Liu, Di Liang, Fang Fang, Sirui Wang, Wei Wu, Rui Jiang
For each given question, TMA first extracts the relevant concepts from the KG, and then feeds them into a multiway adaptive module to produce a \emph{temporal-specific} representation of the question.
no code implementations • 20 Jan 2023 • Luyao Chen, Zhiqiang Chen, Longsheng Jiang, Xiang Liu, Linlu Xu, Bo Zhang, Xiaolong Zou, Jinying Gao, Yu Zhu, Xizi Gong, Shan Yu, Sen Song, Liangyi Chen, Fang Fang, Si Wu, Jia Liu
Nowadays, we have witnessed the great success of AI in various applications, including image classification, game playing, protein structure analysis, language translation, and content generation.
no code implementations • 25 Sep 2022 • Shiyu Jiao, Fang Fang, Zhiguo Ding
The proposed PFP algorithm and the DDPG-based algorithm are compared in the presence of different channel estimation errors.
no code implementations • 9 Mar 2022 • Fang Fang, Shenliao Bao
Modern scientific research and applications very often encounter "fragmentary data" which brings big challenges to imputation and prediction.
no code implementations • 24 Dec 2021 • Chaoxia Yuan, Chao Ying, Zhou Yu, Fang Fang
Support vector machine (SVM) is a powerful classification method that has achieved great success in many fields.
no code implementations • 30 Nov 2021 • Yi Guo, Fang Fang, Donghong Cai, Zhiguo Ding
Simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) has been considered as a promising auxiliary device to enhance the performance of the wireless network, where users located at the different sides of the surfaces can be simultaneously served by the transmitting and reflecting signals.
1 code implementation • 7 Nov 2021 • Ali Syed Saqlain, Li-Yun Wang, Fang Fang
In this paper, we introduce an end-to-end generative adversarial network (GAN) based on sparse learning for single image blind motion deblurring, which we called SL-CycleGAN.
no code implementations • 2 Oct 2021 • Ren Li, Yanan Cao, Qiannan Zhu, Xiaoxue Li, Fang Fang
Modeling of relation pattern is the core focus of previous Knowledge Graph Embedding works, which represents how one entity is related to another semantically by some explicit relation.
1 code implementation • 24 Sep 2021 • Ren Li, Yanan Cao, Qiannan Zhu, Guanqun Bi, Fang Fang, Yi Liu, Qian Li
However, most existing KGE works focus on the design of delicate triple modeling function, which mainly tells us how to measure the plausibility of observed triples, but offers limited explanation of why the methods can extrapolate to unseen data, and what are the important factors to help KGE extrapolate.
Ranked #12 on Link Prediction on FB15k-237
no code implementations • ACL 2021 • Ruipeng Jia, Yanan Cao, Fang Fang, Yuchen Zhou, Zheng Fang, Yanbing Liu, Shi Wang
In this paper, we conceptualize the single-document extractive summarization as a rebalance problem and present a deep differential amplifier framework.
1 code implementation • 5 Jul 2021 • Mingzhou Liu, Xiangyu Zheng, Xinwei Sun, Fang Fang, Yizhou Wang
When this condition fails, we surprisingly find with an example that this whole stable set, although can fully exploit stable information, is not the optimal one to transfer.
no code implementations • 20 Sep 2020 • Arthur S. de Sena, Dick Carrillo, Fang Fang, Pedro H. J. Nardelli, Daniel B. da Costa, Ugo S. Dias, Zhiguo Ding, Constantinos B. Papadias, Walid Saad
Massive multiple-input multiple-output (MIMO) and non-orthogonal multiple access (NOMA) are two key techniques for enabling massive connectivity in future wireless networks.
no code implementations • 14 Sep 2020 • Ximing Xie, Fang Fang, Zhiguo Ding
To address this non-convex problem, we propose an alternating optimization based algorithm.
no code implementations • 14 Sep 2020 • Fang Fang, Kaidi Wang, Zhiguo Ding, Victor C. M. Leung
In this paper, we mainly focus on energy-efficient resource allocation for a multi-user, multi-BS NOMA assisted MEC network with imperfect channel state information (CSI), in which each user can upload its tasks to multiple base stations (BSs) for remote executions.
no code implementations • 11 Sep 2020 • Fang Fang, Yanqing Xu, Zhiguo Ding, Chao Shen, Mugen Peng, George K. Karagiannidis
We adopt the partial offloading policy, in which each user can partition its computation task into offloading and locally computing parts.
no code implementations • 11 Sep 2020 • Fang Fang, Yanqing Xu, Quoc-Viet Pham, Zhiguo Ding
Combining intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) is an effective solution to enhance communication coverage and energy efficiency.
no code implementations • 28 Mar 2020 • Hengzhu Tang, Yanan Cao, Zhen-Yu Zhang, Jiangxia Cao, Fang Fang, Shi Wang, Pengfei Yin
In this paper, we propose a Hierarchical Inference Network (HIN) to make full use of the abundant information from entity level, sentence level and document level.
Ranked #51 on Relation Extraction on DocRED
no code implementations • 13 Apr 2016 • Cheng Chen, Xilin Zhang, Yizhou Wang, Fang Fang
In this study, we propose a novel method to measure bottom-up saliency maps of natural images.
no code implementations • 22 Jul 2013 • Lucas Paletta, Laurent Itti, Björn Schuller, Fang Fang
This volume contains the papers accepted at the 6th International Symposium on Attention in Cognitive Systems (ISACS 2013), held in Beijing, August 5, 2013.