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Learning to select pseudo labels: a semi-supervised method for named entity recognition Research Articles
Zhen-zhen Li, Da-wei Feng, Dong-sheng Li, Xi-cheng Lu,lizhenzhen14@nudt.edu.cn,davyfeng.c@gmail.com,dsli@nudt.edu.cn,xclu@nudt.edu.cn
Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6, Pages 809-962 doi: 10.1631/FITEE.1800743
Keywords: 命名实体识别;无标注数据;深度学习;半监督学习方法
NGAT: attention in breadth and depth exploration for semi-supervised graph representation learning Research Articles
Jianke HU, Yin ZHANG,yinzh@zju.edu.cn
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 3, Pages 409-421 doi: 10.1631/FITEE.2000657
Keywords: Graph learning Semi-supervised learning Node classification Attention
Representation learning via a semi-supervised stacked distance autoencoder for image classification Research Articles
Liang Hou, Xiao-yi Luo, Zi-yang Wang, Jun Liang,jliang@zju.edu.cn
Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7, Pages 963-1118 doi: 10.1631/FITEE.1900116
Keywords: 自动编码器;图像分类;半监督学习;神经网络
Pre-training with asynchronous supervised learning for reinforcement learning based autonomous driving Research Articles
Yunpeng Wang, Kunxian Zheng, Daxin Tian, Xuting Duan, Jianshan Zhou,ypwang@buaa.edu.cn,zhengkunxian@buaa.edu.cn,dtian@buaa.edu.cn,duanxuting@buaa.edu.cn
Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 5, Pages 615-766 doi: 10.1631/FITEE.1900637
Keywords: 自主驾驶;自动驾驶车辆;强化学习;监督学习
A self-supervised method for treatment recommendation in sepsis Research Articles
Sihan Zhu, Jian Pu,jianpu@fudan.edu.cn
Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 7, Pages 926-939 doi: 10.1631/FITEE.2000127
Keywords: 治疗推荐;脓毒症;自监督学习;强化学习;电子病历
Interactive image segmentation with a regression based ensemble learning paradigm Article
Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7, Pages 1002-1020 doi: 10.1631/FITEE.1601401
Keywords: Interactive image segmentation Multivariate adaptive regression splines (MARS) Ensemble learning Thin-plate spline regression (TPSR) Semi-supervised learning Support vector regression (SVR)
Ensemble enhanced active learning mixture discriminant analysis model and its application for semi-supervised fault classification Research Article
Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1814-1827 doi: 10.1631/FITEE.2200053
Keywords: Semi-supervised Active learning Ensemble learning Mixture discriminant analysis Fault classification
Federated unsupervised representation learning Research Article
Fengda ZHANG, Kun KUANG, Long CHEN, Zhaoyang YOU, Tao SHEN, Jun XIAO, Yin ZHANG, Chao WU, Fei WU, Yueting ZHUANG, Xiaolin LI,fdzhang@zju.edu.cn,kunkuang@zju.edu.cn
Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 8, Pages 1181-1193 doi: 10.1631/FITEE.2200268
Keywords: Federated learning Unsupervised learning Representation learning Contrastive learning
Self-supervised graph learning with target-adaptive masking for session-based recommendation Research Article
Yitong WANG, Fei CAI, Zhiqiang PAN, Chengyu SONG,wangyitong20@nudt.edu.cn,caifei08@nudt.edu.cn,panzhiqiang@nudt.edu.cn,songchengyu@nudt.edu.cn
Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 1, Pages 73-87 doi: 10.1631/FITEE.2200137
Keywords: Session-based recommendation Self-supervised learning Graph neural networks Target-adaptive masking
Interactive medical image segmentation with self-adaptive confidence calibration
沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰
Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 9, Pages 1332-1348 doi: 10.1631/FITEE.2200299
Keywords: Medical image segmentation Interactive segmentation Multi-agent reinforcement learning Confidence learning Semi-supervised learning
Correspondence: Uncertainty-aware complementary label queries for active learning Perspective
Shengyuan LIU, Ke CHEN, Tianlei HU, Yunqing MAO,liushengyuan@zju.edu.cn,chenk@cs.zju.edu.cn,htl@zju.edu.cn,myq@citycloud.com.cn
Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 10, Pages 1497-1503 doi: 10.1631/FITEE.2200589
Keywords: 主动学习;图片分类;弱监督学习
Learning-based parameter prediction for quality control in three-dimensional medical image compression Research Articles
Yuxuan Hou, Zhong Ren, Yubo Tao, Wei Chen,3140104190@zju.edu.cn,renzhong@cad.zju.edu.cn
Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 9, Pages 1169-1178 doi: 10.1631/FITEE.2000234
Keywords: 医学图像压缩;高效视频编码(HEVC);质量控制;基于学习方法
Yue Hou, Qiuhan Li, Chen Zhang, Guoyang Lu, Zhoujing Ye, Yihan Chen, Linbing Wang, Dandan Cao
Engineering 2021, Volume 7, Issue 6, Pages 845-856 doi: 10.1016/j.eng.2020.07.030
In modern transportation, pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians. Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users. Therefore, monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance, which in turn ensures public transportation safety. Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions. Advanced technologies can be employed for the collection and analysis of such data, including various intrusive sensing techniques, image processing techniques, and machine learning methods. This review summarizes the state-of-the-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.
Keywords: Pavement monitoring and analysis The state-of-the-art review Intrusive sensing Image processing techniques Machine learning methods
Pattern Recognition With Fuzzy Central Clustering Algorithms
Zen Huanglin,Yuan Hui,Liu Xiaofang
Strategic Study of CAE 2004, Volume 6, Issue 11, Pages 33-37
Based on optimization of constrained nonlinear programming, an approach of clustering center and a fuzzy membership function of pattern classification are derived from an objective function of the constrained nonlinear programming. An unsupervised algorithm with recursive expression and a fuzzy central cluster neural network are suggested in this paper. The fuzzy central cluster neural network proposed here can realize crisp decision or fuzzy decision in pattern classification.
Keywords: fuzzy sets central cluster pattern recognition neural network
Unsupervised feature selection via joint local learning and group sparse regression Regular Papers
Yue WU, Can WANG, Yue-qing ZHANG, Jia-jun BU
Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 4, Pages 538-553 doi: 10.1631/FITEE.1700804
Feature selection has attracted a great deal of interest over the past decades. By selecting meaningful feature subsets, the performance of learning algorithms can be effectively improved. Because label information is expensive to obtain, unsupervised feature selection methods are more widely used than the supervised ones. The key to unsupervised feature selection is to find features that effectively reflect the underlying data distribution. However, due to the inevitable redundancies and noise in a dataset, the intrinsic data distribution is not best revealed when using all features. To address this issue, we propose a novel unsupervised feature selection algorithm via joint local learning and group sparse regression (JLLGSR). JLLGSR incorporates local learning based clustering with group sparsity regularized regression in a single formulation, and seeks features that respect both the manifold structure and group sparse structure in the data space. An iterative optimization method is developed in which the weights finally converge on the important features and the selected features are able to improve the clustering results. Experiments on multiple real-world datasets (images, voices, and web pages) demonstrate the effectiveness of JLLGSR.
Keywords: Unsupervised Local learning Group sparse regression Feature selection
Title Author Date Type Operation
Learning to select pseudo labels: a semi-supervised method for named entity recognition
Zhen-zhen Li, Da-wei Feng, Dong-sheng Li, Xi-cheng Lu,lizhenzhen14@nudt.edu.cn,davyfeng.c@gmail.com,dsli@nudt.edu.cn,xclu@nudt.edu.cn
Journal Article
NGAT: attention in breadth and depth exploration for semi-supervised graph representation learning
Jianke HU, Yin ZHANG,yinzh@zju.edu.cn
Journal Article
Representation learning via a semi-supervised stacked distance autoencoder for image classification
Liang Hou, Xiao-yi Luo, Zi-yang Wang, Jun Liang,jliang@zju.edu.cn
Journal Article
Pre-training with asynchronous supervised learning for reinforcement learning based autonomous driving
Yunpeng Wang, Kunxian Zheng, Daxin Tian, Xuting Duan, Jianshan Zhou,ypwang@buaa.edu.cn,zhengkunxian@buaa.edu.cn,dtian@buaa.edu.cn,duanxuting@buaa.edu.cn
Journal Article
A self-supervised method for treatment recommendation in sepsis
Sihan Zhu, Jian Pu,jianpu@fudan.edu.cn
Journal Article
Interactive image segmentation with a regression based ensemble learning paradigm
Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU
Journal Article
Ensemble enhanced active learning mixture discriminant analysis model and its application for semi-supervised fault classification
Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE
Journal Article
Federated unsupervised representation learning
Fengda ZHANG, Kun KUANG, Long CHEN, Zhaoyang YOU, Tao SHEN, Jun XIAO, Yin ZHANG, Chao WU, Fei WU, Yueting ZHUANG, Xiaolin LI,fdzhang@zju.edu.cn,kunkuang@zju.edu.cn
Journal Article
Self-supervised graph learning with target-adaptive masking for session-based recommendation
Yitong WANG, Fei CAI, Zhiqiang PAN, Chengyu SONG,wangyitong20@nudt.edu.cn,caifei08@nudt.edu.cn,panzhiqiang@nudt.edu.cn,songchengyu@nudt.edu.cn
Journal Article
Interactive medical image segmentation with self-adaptive confidence calibration
沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰
Journal Article
Correspondence: Uncertainty-aware complementary label queries for active learning
Shengyuan LIU, Ke CHEN, Tianlei HU, Yunqing MAO,liushengyuan@zju.edu.cn,chenk@cs.zju.edu.cn,htl@zju.edu.cn,myq@citycloud.com.cn
Journal Article
Learning-based parameter prediction for quality control in three-dimensional medical image compression
Yuxuan Hou, Zhong Ren, Yubo Tao, Wei Chen,3140104190@zju.edu.cn,renzhong@cad.zju.edu.cn
Journal Article
The State-of-the-Art Review on Applications of Intrusive Sensing, Image Processing Techniques, and Machine Learning Methods in Pavement Monitoring and Analysis
Yue Hou, Qiuhan Li, Chen Zhang, Guoyang Lu, Zhoujing Ye, Yihan Chen, Linbing Wang, Dandan Cao
Journal Article
Pattern Recognition With Fuzzy Central Clustering Algorithms
Zen Huanglin,Yuan Hui,Liu Xiaofang
Journal Article