Exploring Groups from Heterogeneous Data via Sparse Learning

机译：通过稀疏学习探索来自异构数据的群组

获取原文

页面导航

摘要
著录项
相似文献
相关主题

摘要

Complexity networks, such as social networks, biological networks and co-citation networks, are ubiquitous in reality. Identifying groups from data is critical for network analysis, for it can offer deep insights in understanding the structural properties and functions of complex networks. Over the past decades, many endeavors from interdisciplinary fields have been attempted to identify groups from data. However, little attention has been paid on exploring groups and their relationships from different views. In this work, we address this issue by using canonical correlation analysis (CCA) to analyze groups and their interplays in the networks. To further improve the interpretability of results, we solve the optimization problem with sparse learning, and then propose a generalized framework of group discovery from heterogeneous data. This framework enables us to find groups and explicitly model their relationships from diverse views simultaneously. Extensive experimental studies conducted on both synthetic and DBLP datasets demonstrate the effectiveness of the proposed method.

机译：复杂性网络，例如社交网络，生物网络和共同引用网络，现实中无处不在。识别来自数据的组对于网络分析至关重要，因为它可以为了解复杂网络的结构性和功能而提供深度洞察。在过去的几十年中，已经尝试从跨学科领域的许多努力识别来自数据的组。但是，从不同意见的探索群体和关系中，已经提出了很少的关注。在这项工作中，我们通过使用规范相关性分析（CCA）来分析组及其在网络中的相互作用来解决此问题。为了进一步提高结果的可解释性，我们解决了稀疏学习的优化问题，然后从异构数据提出了集团发现的广义框架。此框架使我们能够同时查找组并明确地模拟与不同视图的关系。在合成和DBLP数据集上进行的广泛实验研究表明了该方法的有效性。

著录项

来源
《Pacific-Asia conference on advances in knowledge discovery and data mining》|2013年||共12页
会议地点
作者
Huawen Liu; Jiuyong Li; Lin Liu; Jixue Liu; Ivan Lee; Jianmin Zhao;
展开▼
作者单位

展开▼
会议组织
原文格式 PDF
正文语种
中图分类 TP311.13;
关键词
Group discovery; complexity network; canonical correlation analysis; LASSO; Sparse learning;

机译：小组发现;复杂网络;规范相关分析;套索;稀疏学习;

相似文献

外文文献
中文文献
专利

1. Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning [J] . Wang Hua, Nie Feiping, Huang Heng, Bioinformatics . 2012,第12期

机译：通过稀疏多模式多任务学习从多维异质成像遗传学数据中识别疾病敏感和与数量相关的与特征相关的生物标记
2. Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging geneticsn data via sparse multimodal multitask learning [J] . Bioinformatics . 2012,第12期

机译：通过稀疏多模态多任务学习从多维异质成像遗传学数据中识别疾病敏感性和数量性状相关的生物标记
3. TREVOR HASTIE, ROBERT TIBSHIRANI, AND MARTIN WAINWRIGHT . Statistical Learning with Sparsity: The Lasso and Generalizations . Boca Raton : CRC Press . TREVOR HASTIE, ROBERT TIBSHIRANI, AND MARTIN WAINWRIGHT TREVOR HASTIE, ROBERT TIBSHIRANI, AND MARTIN WAINWRIGHT . Statistical Learning with Sparsity: The Lasso and Generalizations Statistical Learning with Sparsity: The Lasso and Generalizations . Boca Raton Boca Raton : CRC Press CRC Press . [J] . Kondofersky Ivan, Theis Fabian J. Biometrics: Journal of the Biometric Society : An International Society Devoted to the Mathematical and Statistical Aspects of Biology . 2018,第2期

机译：Trevor Hastie，Robert Tibshirani和Martin Wainwright。统计学习稀疏性：套索和概括。 Boca Raton：CRC压力机。 Trevor Hastie，Robert Tibshirani和Martin Wainwright Trevor Hastie，Robert Tibshirani和Martin Wainwright。统计学习与稀疏性：套索与稀疏性统计学习：套索和概括。 Boca Raton Boca Raton：CRC按CRC压力机。
4. Exploring Groups from Heterogeneous Data via Sparse Learning [C] . Huawen Liu, Jiuyong Li, Lin Liu, Advances in knowledge discovery and data mining . 2013

机译：通过稀疏学习从异构数据中探索群体
5. Sparse and large-scale learning models and algorithms for mining heterogeneous big data. [D] . Cai, Xiao. 2013

机译：用于挖掘异构大数据的稀疏大规模学习模型和算法。
6. Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning [O] . Hua Wang, Feiping Nie, Heng Huang, -1

机译：通过稀疏多模式多任务学习从多维异质成像遗传学数据中识别疾病敏感和与数量性状相关的生物标记
7. Tackling ordinal regression problem for heterogeneous data: sparse and deep multi-task learning approaches [O] . Lu Wang, Dongxiao Zhu 2021

机译：解决异构数据的序数回归问题：稀疏和深度多任务学习方法

Exploring Groups from Heterogeneous Data via Sparse Learning

摘要

著录项

相似文献

相关主题

期刊订阅