Projects
Reading
People
Chat
SU\G
(𝔸)
/K·U
Projects
Reading
People
Chat
Sign Up
Light
Dark
System
The Informativeness of k-Means for Learning Gaussian Mixture Models.
Zhaoqiang Liu
,
Vincent Y. F. Tan
Type:
Article
Publication Date:
2017-03-30
Citations:
0
View Publication
Share
Locations
arXiv (Cornell University) -
View
Similar Works
Action
Title
Year
Authors
+
The Informativeness of $k$-Means for Learning Mixture Models
2017
Zhaoqiang Liu
Vincent Y. F. Tan
+
The Informativeness of $k$-Means and Dimensionality Reduction for Learning Mixture Models
2017
Zhaoqiang Liu
Vincent Y. F. Tan
+
PDF
Chat
The Informativeness of k-Means for Learning Mixture Models
2018
Zhaoqiang Liu
Vincent Y. F. Tan
+
PDF
Chat
The Informativeness of $k$ -Means for Learning Mixture Models
2019
Zhaoqiang Liu
Vincent Y. F. Tan
+
Learning Mixtures of Gaussians using the k-means Algorithm
2009
Kamalika Chaudhuri
Sanjoy Dasgupta
Andrea Vattani
+
High dimensional clustering for mixture models
2020
Yiming Liu
+
Algorithms for finding k in k-means.
2020
Chiranjib Bhattacharyya
Ravindran Kannan
Amit Kumar
+
PDF
Chat
Clustering with Spectral Norm and the k-Means Algorithm
2010
Amit Kumar
Ravindran Kannan
+
Clustering with Spectral Norm and the k-means Algorithm
2010
Amit Kumar
Ravindran Kannan
+
Estimation of mixture models
1999
Q. Li
Andrew R. Barron
+
Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation
2013
Martin Azizyan
Aarti Singh
Larry Wasserman
+
Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation
2013
Martin Azizyan
Aarti Singh
Larry Wasserman
+
Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation
2013
Martin Azizyan
Aarti Singh
Larry Wasserman
+
Linear Time Clustering for High Dimensional Mixtures of Gaussian Clouds
2017
Dan Kushnir
Shirin Jalali
Iraj Saniee
+
Clustering with Spectral Norm and the k-means Algorithm
2010
Amit Kumar
Ravindran Kannan
+
Tight bounds for learning a mixture of two gaussians
2014
Moritz Hardt
Eric Price
+
Tight bounds for learning a mixture of two gaussians
2014
Moritz Hardt
Eric Price
+
A Nearly Optimal and Agnostic Algorithm for Properly Learning a Mixture of k Gaussians, for any Constant k
2015
Jerry Zheng Li
Ludwig Schmidt
+
Nearly Optimal Clustering Risk Bounds for Kernel K-Means
2020
Yong Liu
Lizhong Ding
Weiping Wang
+
Monte Carlo approximation certificates for k-means clustering
2017
Dustin G. Mixon
Soledad Villar
Works That Cite This (0)
Action
Title
Year
Authors
Works Cited by This (0)
Action
Title
Year
Authors