新闻
  19.7.23
ScholarSpace计算机中文文献导读已更新到2019年6月!
  19.5.9
计算机学科排名系统ScholarRankings v2.0发布,新增领域选择和排名方式选择功能。
  19.4.27
学术引用系统ScholarCitation v1.0发布,基于计算机领域82826篇期刊论文间的引用关系,评估学术影响力。
  18.1.9
计算机学科排名系统ScholarRankings v1.0发布,其旨在改善原有排名方法,激励国内高校和教师积极参与计算机各个领域的研究,学者与学校的排名不仅取决于论文数量,排名结果更具有参考性(排名算法参考CSRankings)。
  17.11.9
学者关系知识图谱ScholarGraph v1.0发布,涵盖七大领域(计算机、经济、管理、物理、地理、考古、教育)673,044位学者、1,068,928篇论文的数据,共计10,612,497个三元组,每个领域下均有作者、期刊、论文、论文实体,以及论文发表、论文出版关系等。
  17.10.25
学者谱系检索系统ScholarTree(DegreeTree v2.0)系统发布,现已收录53个领域4,003,276条学位论文(涉及53个领域),挖掘出4,643,028条师生关系。

燕锋    Yan Feng


中南大学信息科学与工程学院



研究领域:


研究兴趣:

共检索到结果2条  被引1次[注:ScholarSpace内自引数]
查看燕锋的合作作者    在DBLP中查找该作者文献
查看该作者的单位历史    作者项目历史

论文列表


注:被引数指ScholarSpace内自引数
No. 论文信息 领域 被引数
2016
2 沈连丰 朱亚萍 丁兆明 燕锋 邓曙光 . 软件定义传感器网络重配置算法研究. 通信学报, 2016, (07): 计算机网络 1
2011
1 龙昊 王国军 燕锋 . 普适家庭医疗系统中的隐私保护模型. 计算机工程, 2011, (03): 287-290网络与信息安全 0

DBLP检索到的论文列表

No. Paper Inforamtion
2014
1 Feng Yan, Ludmila Cherkasova, Zhuoyao Zhang, Evgenia Smirni, Heterogeneous cores for MapReduce processing: Opportunity or challenge? NOMS, 2014
0 Feng Yan, Philippe Martins, Laurent Decreusefond, Accuracy of Homology Based Coverage Hole Detection for Wireless Sensor Networks on Sphere. IEEE Transactions on Wireless Communications, 2014, IEEE Transactions on Wireless Communications, 13(7): 3583-3595
2013
-1 Feng Yan, Shannon Hughes, Alma Riska, Evgenia Smirni, Overcoming Limitations of Off-the-Shelf Priority Schedulers in Dynamic Environments. MASCOTS, 2013
-2 Feng Yan, Shreyas Sundaram, S. V. N. Vishwanathan, Yuan Qi, Distributed Autonomous Online Learning: Regrets and Intrinsic Privacy-Preserving Properties. IEEE Trans. Knowl. Data Eng., 2013, IEEE Trans. Knowl. Data Eng., 25(11): 2483-2493
2012
-3 Zenglin Xu, Feng Yan, Alan Qi, Infinite Tucker Decomposition: Nonparametric Bayesian Models for Multiway Data Analysis. ICML, 2012
-4 Feng Yan, Philippe Martins, Laurent Decreusefond, Accuracy of homology based approaches for coverage hole detection in wireless sensor networks. ICC, 2012
2011
-5 Zenglin Xu, Feng Yan, Yuan Qi, Sparse Matrix-Variate t Process Blockmodels. AAAI, 2011
-6 Feng Yan, Xenia Mountrouidou, Alma Riska, Evgenia Smirni, Toward Automating Work Consolidation with Performance Guarantees in Storage Clusters. MASCOTS, 2011
-7 Yuan (Alan) Qi, Feng Yan, EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning. NIPS, 2011
-8 Feng Yan, Zenglin Xu, Yuan (Alan) Qi, Sparse matrix-variate Gaussian process blockmodels for network modeling. UAI, 2011
2010
-9 Tianji Wu, Bo Wang, Yi Shan, Feng Yan, Yu Wang 0002, Ningyi Xu, Efficient PageRank and SpMV Computation on AMD GPUs. ICPP, 2010
-10 Feng Yan, Yuan (Alan) Qi, Sparse Gaussian Process Regression via L1 Penalization. ICML, 2010
2009
-11 Bo Wang, Tianji Wu, Feng Yan, Ruirui Li, Ningyi Xu, Yu Wang 0002, RankBoost Acceleration on both NVIDIA CUDA and ATI Stream Platforms. ICPADS, 2009
-12 Feng Yan, Ningyi Xu, Yuan Qi, Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units. NIPS, 2009
2008
-13 Wen-Chi Hou, Cheng Luo, Zhewei Jiang, Feng Yan, Qiang Zhu, Approximate Range-Sum Queries over Data Cubes Using Cosine Transform. DEXA, 2008
2006
-14 Zhewei Jiang, Cheng Luo, Wen-Chi Hou, Feng Yan, Qiang Zhu, Estimating Aggregate Join Queries over Data Streams Using Discrete Cosine Transform. DEXA, 2006
-15 Cheng Luo, Zhewei Jiang, Wen-Chi Hou, Feng Yan, Chih-Fang Wang, Estimating XML Structural Join Size Quickly and Economically. ICDE, 2006
2005
-16 Hong Guo, Wen-Chi Hou, Feng Yan, Qiang Zhu, A Metropolis Sampling Method for Drawing Representative Samples from Large Databases. DASFAA, 2005
2004
-17 Hong Guo, Wen-Chi Hou, Feng Yan, Qiang Zhu, A Monte Carlo Sampling Method for Drawing Representative Samples from Large Databases. SSDBM, 2004
2003
-18 Feng Yan, Wen-Chi Hou, Qiang Zhu, Selectivity Estimation Using Orthogonal Series. DASFAA, 2003

合作作者列表

1 丁兆明 [2]  
2 朱亚萍 [2]  
3 沈连丰 [2]  
4 王国军 [1]  
5 邓曙光 [2]  
6 龙昊 [1]  

单位历史信息

中南大学信息科学与工程学院 (2011--2011)
东南大学移动通信国家重点实验室 (2016--2016)

说明: 作者的单位历史信息是根据本系统中论文的单位信息采用算法自动计算得到,部分信息可能不准确,仅供参考。