Composable core-sets for determinant maximization: A simple near-optimal algorithm
"Composable core-sets" are an efficient framework for solving optimization problems in massive data models. In this work, we consider efficient construction of composable core-sets for the determinant maximization problem. This can also be cast as the MAP inference task for determinantal p...
Main Author: | Indyk, Piotr (Author) |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor) |
Format: | Article |
Language: | English |
Published: |
International Machine Learning Society (IMLS),
2021-01-15T15:06:10Z.
|
Subjects: | |
Online Access: | Get fulltext |
Similar Items
-
Composable core-sets for determinant maximization problems via spectral spanners
by: Indyk, Piotr
Published: (2021) -
Composable core-sets for diversity and coverage maximization
by: Indyk, Piotr, et al.
Published: (2018) -
Nearly optimal deterministic algorithm for sparse Walsh-Hadamard transform
by: Cheraghchi, Mahdi, et al.
Published: (2018) -
Near-Optimal Convergent Approach for Composed Influence Maximization Problem in Social Networks
by: Jianming Zhu, et al.
Published: (2019-01-01) -
Near-optimal (euclidean) metric compression
by: Indyk, Piotr, et al.
Published: (2018)