Co-regularized weighting multiview clustering
نویسندگان
چکیده
منابع مشابه
Regularized Co-Clustering on Manifold
Co-clustering is to partition rows and columns of a matrix simultaneously. It has been an important research field in data mining and machine learning. It is preferred over traditional homogeneous clustering techniques in many real applications. In this paper, we present a co-clustering algorithm based on local information and regularization. The algorithm seeks to preserve the local intrinsic ...
متن کاملCo-regularized PLSA for Multi-view Clustering
Multi-view data is common in a wide variety of application domains. Properly exploiting the relations among different views is helpful to alleviate the difficulty of a learning problem of interest. To this end, we propose an extended Probabilistic Latent Semantic Analysis (PLSA) model for multi-view clustering, named Co-regularized PLSA (CoPLSA). CoPLSA integrates individual PLSAs in different ...
متن کاملCo-regularized Multi-view Spectral Clustering
In many clustering problems, we have access to multiple views of the data each of which could be individually used for clustering. Exploiting information from multiple views, one can hope to find a clustering that is more accurate than the ones obtained using the individual views. Often these different views admit same underlying clustering of the data, so we can approach this problem by lookin...
متن کاملCo-regularized Spectral Clustering with Multiple Kernels
We propose a co-regularization based multiview spectral clustering algorithm which enforces the clusterings across multiple views to agree with each-other. Since each view can be used to define a similarity graph over the data, our algorithm can also be considered as learning with multiple similarity graphs, or equivalently with multiple kernels. We propose an objective function that implicitly...
متن کاملRegularized Co-Clustering with Dual Supervision
By attempting to simultaneously partition both the rows (examples) and columns (features) of a data matrix, Co-clustering algorithms often demonstrate surprisingly impressive performance improvements over traditional one-sided row clustering techniques. A good clustering of features may be seen as a combinatorial transformation of the data matrix, effectively enforcing a form of regularization ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Algorithms & Computational Technology
سال: 2017
ISSN: 1748-3026,1748-3026
DOI: 10.1177/1748301817701027