Scalable and globally optimal generalized L1 K-center clustering via constraint generation in mixed integer linear programming
The k-center clustering algorithm, introduced over 35 years ago, is known to be robust to class imbalance prevalent in many clustering problems and has various applications such as data summarization, document clustering, and facility location determination. Unfortunately, existing k-center algorith...
Saved in:
Main Authors: | CHEMBU, Aravinth, SANNER, Scott, KHURRAM, Hassan, KUMAR, Akshat |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2023
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/8518 https://ink.library.smu.edu.sg/context/sis_research/article/9521/viewcontent/aaai23_kcenters.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Scalable and globally optimal generalized L1 K-center clustering via constraint generation in mixed integer linear programming
by: CHEMBU, Aravinth, et al.
Published: (2023) -
Determination of the port attractiveness using mixed integer linear programming method
by: Kramberger, T., et al.
Published: (2016) -
Distributionally robust mixed integer linear programs: Persistency models with applications
by: Li, X., et al.
Published: (2014) -
A stochastic optimization formulation of unit commitment with reliability constraints
by: Xiong, P., et al.
Published: (2014) -
Comparison of optimization frameworks for the design of a multi-energy microgrid
by: Rigo-Mariani, Rémy, et al.
Published: (2021)