no code implementations • 16 Nov 2023 • Yipei Xu, Dakuan Lu, Jiaqing Liang, Xintao Wang, Yipeng Geng, Yingsi Xin, Hengkui Wu, Ken Chen, ruiji zhang, Yanghua Xiao
Pre-trained language models (PLMs) have established the new paradigm in the field of NLP.
no code implementations • 6 Apr 2021 • Yuhang Gai, Jiuming Guo, Dan Wu, Ken Chen
Reinforcement learning (RL) is always the preferred embodiment to construct the control strategy of complex tasks, like asymmetric assembly tasks.
no code implementations • 30 Mar 2021 • Yuhang Gai, Jiuming Guo, Dan Wu, Ken Chen
This paper aims at solving mass precise peg-in-hole assembly.
no code implementations • 10 Dec 2020 • Mustafa Othman, Ken Chen, Anissa Mokraoui
This mechanism impacts greatly on the overall Quality of Experience (QoE) of the video streaming.
SSIM Multimedia
no code implementations • CVPR 2019 • Ken Chen, Yichao Wu, Haoyu Qin, Ding Liang, Xuebo Liu, Junjie Yan
The core of this problem is to make features extracted from different models comparable.
no code implementations • 27 May 2019 • Zhenmao Li, Yichao Wu, Ken Chen, Yudong Wu, Shunfeng Zhou, Jiaheng Liu, Junjie Yan
Example weighting algorithm is an effective solution to the training bias problem, however, most previous typical methods are usually limited to human knowledge and require laborious tuning of hyperparameters.
no code implementations • 5 Dec 2018 • Ken Chen, Fei Chen, Baisheng Lai, Zhongming Jin, Yong liu, Kai Li, Long Wei, Pengfei Wang, Yandong Tang, Jianqiang Huang, Xian-Sheng Hua
To capture the graph dynamics, we use the graph prediction stream to predict the dynamic graph structures, and the predicted structures are fed into the flow prediction stream.
no code implementations • 12 Sep 2018 • Liheng Chen, Yanru Qu, Zhenghui Wang, Lin Qiu, Wei-Nan Zhang, Ken Chen, Shaodian Zhang, Yong Yu
TGE-PS uses Pairs Sampling (PS) to improve the sampling strategy of RW, being able to reduce ~99% training samples while preserving competitive performance.
no code implementations • NAACL 2018 • Zhenghui Wang, Yanru Qu, Li-Heng Chen, Jian Shen, Wei-Nan Zhang, Shaodian Zhang, Yimei Gao, Gen Gu, Ken Chen, Yong Yu
We study the problem of named entity recognition (NER) from electronic medical records, which is one of the most fundamental and critical problems for medical text mining.
Medical Named Entity Recognition named-entity-recognition +3