Local Search Methods for k-Means with Outliers
By Shalmoli Gupta, Ravi Kumar, Kefu Lu, Benjamin Moseley, Sergei Vassilvitskii. 2017
114 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability, Algorithms & Complexity
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Han-Jia Ye
- De-chuan Zhan
- Richard S. Zemel
- Sergey Levine
- Josh Tenenbaum
- Yoshua Bengio
- Quoc V. Le
- Trevor Darrell
In Statistics and Probability
- Kannan Ramchandran
- Kevin Swersky
- Josh Tenenbaum
- Hugo Larochelle
- Richard S. Zemel
- Avishek Ghosh
- Justin Hong
- Jake Snell
In Algorithms & Complexity
Citations in the corpus
- Meta-Learning for Semi-Supervised Few-Shot Classification (2018, methodology): “In addition to the original k -Means method (Lloyd, 1982), the most related work to our setup involving clustering algorithms considers applying k -Means in the presence of outliers (Hautamäki et al., 2005; Chawla & Gionis, 2013; Gupta et al., 2017).”
- Robust Federated Learning in a Heterogeneous Environment (2019, background): “[29] Shalmoli Gupta, Ravi Kumar, Kefu Lu, Benjamin Moseley, and Sergei Vassilvitskii.”