Spectral ensemble clustering via weighted k-means: Theoretical and practical evidence

H Liu, J Wu, T Liu, D Tao, Y Fu - IEEE transactions on …, 2017 - ieeexplore.ieee.org
As a promising way for heterogeneous data analytics, consensus clustering has attracted
increasing attention in recent decades. Among various excellent solutions, the co …
被引用次数：207 相关文章

Spectral Ensemble Clustering via Weighted K-Means: Theoretical and Practical Evidence

H Liu, J Wu, T Liu, D Tao, Y Fu - IEEE Transactions on Knowledge and …, 2017 - dl.acm.org
As a promising way for heterogeneous data analytics, consensus clustering has attracted
increasing attention in recent decades. Among various excellent solutions, the co …

Spectral Ensemble Clustering via Weighted K-Means: Theoretical and Practical Evidence

H Liu, J Wu, T Liu, D Tao, Y Fu - IEEE Transactions on …, 2017 - opus.lib.uts.edu.au
OPUS at UTS: Spectral Ensemble Clustering via Weighted K-Means: Theoretical and Practical
Evidence - Open Publications of UTS Scholars Skip navigation OPUS at UTS | Open …
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[PDF][PDF] Spectral Ensemble Clustering via Weighted K-means: Theoretical and Practical Evidence

H Liu, J Wu, T Liu, D Tao, Y Fu - ieeexplore.ieee.org
As a promising way for heterogeneous data analytics, consensus clustering has attracted
increasing attention in recent decades. Among various excellent solutions, the co …

Spectral Ensemble Clustering via Weighted K-Means: Theoretical and Practical Evidence

H Liu, J Wu, T Liu, D Tao, Y Fu - IEEE Transactions on Knowledge & …, 2017 - computer.org
As a promising way for heterogeneous data analytics, consensus clustering has attracted
increasing attention in recent decades. Among various excellent solutions, the co …