Skip to main navigation
Skip to search
Skip to main content
University of Haifa Home
Update your profile
Link opens in a new tab
Search content at University of Haifa
Home
Researchers
Research units
Research output
Training Gaussian mixture models at scale via coresets
Mario Lucic
, Matthew Faulkner
, Andreas Krause
,
Dan Feldman
Department of Computer Science
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Research output
(1)
Fingerprint
Dive into the research topics of 'Training Gaussian mixture models at scale via coresets'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Computer Science
Approximation (Algorithm)
100%
Good Approximation
100%
Computational Geometry
100%
Gaussian Mixture Model
100%
Statistical Estimation
100%
Generating Process
100%
Small Data Set
100%
Complexity Result
100%
Gaussian Mixture
100%
Keyphrases
Gaussian Mixture
100%
Gaussian Mixture Model
100%
Computationally Intensive
33%
Model Fitting
33%
Statistical Estimation
33%
Approximation Error
33%
Computational Geometry
33%
Small Dataset
33%
Massive Datasets
33%
Set Size
33%
Training Time
33%
Complexity Results
33%
Combinatorial Complexity
33%
Mixture Components
33%
Data Generating Process
33%
Statistical Mixture Models
33%
World Data
33%
Mathematics
Gaussian Distribution
100%
Gaussian Mixture Model
100%
Polynomial
33%
Good Approximation
33%
Approximation Error
33%
Real-World Data
33%
Mixture Model
33%
Set Size
33%
Original Data Set
33%