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STATISTICALLY OPTIMAL K-MEANS CLUSTERING VIA NONNEGATIVE LOW-RANK SEMIDEFINITE PROGRAMMING
Yubo Zhuang
,
Xiaohui Chen
,
Yun Yang
,
Richard Y. Zhang
Statistics
Electrical and Computer Engineering
Coordinated Science Lab
Research output
:
Contribution to conference
›
Paper
›
peer-review
Overview
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Dive into the research topics of 'STATISTICALLY OPTIMAL K-MEANS CLUSTERING VIA NONNEGATIVE LOW-RANK SEMIDEFINITE PROGRAMMING'. Together they form a unique fingerprint.
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Keyphrases
Low-rank
100%
K-means
100%
Semidefinite Programming
100%
Statistical Optimality
50%
Optimality Guarantee
50%
Non-negative Matrix Factorization
50%
Nonconvex
25%
Optimization Problem
25%
Clustering Algorithm
25%
Rank Constraint
25%
Existing State
25%
Machine Learning Techniques
25%
Semidefinite Relaxation
25%
Machine Learning
25%
Factorization Method
25%
Clustering Error
25%
Programming Solver
25%
Non-negative Matrix Factorization Algorithm
25%
Burer-Monteiro Factorization
25%
Computer Science
K-Means Clustering
100%
Semidefinite Programming
100%
nonnegative matrix factorization
60%
Machine Learning
40%
Learning System
40%
Large Data Set
20%
Optimization Problem
20%
Clustering Algorithm
20%
Factorization Algorithm
20%
Learning Practitioner
20%