Duality between Feature Selection and Data Clustering

2016-09-27 · Chung Chan, Ali Al-Bashabsheh, Qiaoqiao Zhou, Tie Liu

The feature-selection problem is formulated from an information-theoretic perspective. We show that the problem can be efficiently solved by an extension of the recently proposed info-clustering paradigm. This reveals the fundamental duality between feature selection and data clustering,which is a consequence of the more general duality between the principal partition and the principal lattice of partitions in combinatorial optimization.

📄 PDF Abstract BibTeX arXiv:1609.08312

Code (0)

등록된 구현이 없습니다.

Tasks

ClusteringCombinatorial Optimizationfeature selection

Unsupervised Optimisation of GNNs for Node Clustering

2024-02-12 · William Leeney, Ryan McConville

Graph Neural Networks (GNNs) can be trained to detect communities within a graph by learning from the duality of feature and connectivity information. Currently, the common approach for optimisation of GNNs is to use com…

Clustering graph partitioning Model Selection Node Clustering

Learning A Structured Optimal Bipartite Graph for Co-Clustering

2017-12-01 · NeurIPS 2017 12 · Feiping Nie, Xiaoqian Wang, Cheng Deng, Heng Huang

Co-clustering methods have been widely applied to document clustering and gene expression analysis. These methods make use of the duality between features and samples such that the co-occurring structure of sample and fe…

Clustering

Integer Programming Relaxations for Integrated Clustering and Outlier Detection

2014-03-06 · Lionel Ott, Linsey Pang, Fabio Ramos, David Howe 외

In this paper we present methods for exemplar based clustering with outlier selection based on the facility location formulation. Given a distance function and the number of outliers to be found, the methods automaticall…

Clustering Outlier Detection

Multi-View Multiple Clustering

2019-05-13 · Shixing Yao, Guoxian Yu, Jun Wang, Carlotta Domeniconi 외

Multiple clustering aims at exploring alternative clusterings to organize the data into meaningful groups from different perspectives. Existing multiple clustering algorithms are designed for single-view data. We assume …

Clustering Representation Learning

On the Duality between Network Flows and Network Lasso

2019-10-04 · Alexander Jung

Many applications generate data with an intrinsic network structure such as time series data, image data or social network data. The network Lasso (nLasso) has been proposed recently as a method for joint clustering and …

Clustering Time Series Time Series Analysis