Submodular Maximization Subject to a Knapsack Constraint Under Noise Models
The field of Submodular Maximization subject to a Knapsack constraint has recently expanded to a variety of application domains, which is facing some challenges such as data explosions or additional conditions. There exist plenty of objective functions that cannot be evaluated exactly in many real c...
Saved in:
Main Authors: | Dung, T. K. Ha, Canh, V. Pham, Huan, X. Hoang |
---|---|
Format: | Bài trích |
Language: | English |
Published: |
World Scientific Publishing
2022
|
Subjects: | |
Online Access: | https://www.worldscientific.com/doi/abs/10.1142/S0217595922500130 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5767 https://doi.org/10.1142/S0217595922500130 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Submodular Maximization Subject to a Knapsack Constraint Under Noise Models
by: Dung T. K. Ha | Canh V. Pham, et al.
Published: (2022) -
Optimal dividends under a drawdown constraint and a curious square-root rule
by: Hansjörg, Albrecher, et al.
Published: (2023) -
Inexact penalty decomposition methods for optimization problems with geometric constraints
by: Christian, Kanzow, et al.
Published: (2023) -
Multi-layer noise reshaping and perceptual optimization for effective adversarial attack of images
by: Zhiquan, He, et al.
Published: (2023) -
On a multistage discrete stochastic optimization problem with stochastic constraints and nested sampling
by: Thuy Anh Ta, et al.
Published: (2021)