Results 1 to 10 of about 5,146,266 (215)

Planning with Submodular Objective Functions

CoRR, 2020
We study planning with submodular objective functions, where instead of maximizing the cumulative reward, the goal is to maximize the objective value induced by a submodular function. Our framework subsumes standard planning and submodular maximization with cardinality constraints as special cases, and thus many practical applications can be naturally ...
Ruosong Wang, Hanrui Zhang 0001, Devendra Singh Chaplot, Denis Garagic, Ruslan Salakhutdinov   +4 more
openaire   +2 more sources

Two-Stage Submodular Maximization Under Knapsack Problem

Tsinghua Science and Technology
Two-stage submodular maximization problem under cardinality constraint has been widely studied in machine learning and combinatorial optimization. In this paper, we consider knapsack constraint.
Zhicheng Liu, Jing Jin, Donglei Du, Xiaoyan Zhang   +3 more
doaj   +1 more source

A balanced sensor scheduling for multitarget localization in a distributed multiple-input multiple-output radar network

International Journal of Distributed Sensor Networks, 2021
In this article, we consider the problem of optimally selecting a subset of transmitters from a transmitter set available to a multiple-input and multiple-output radar network.
Chenggang Wang, Zengfu Wang, Xiong Xu, Yuhang Hao   +3 more
doaj   +1 more source

Greedy Sensor Selection for Weighted Linear Least Squares Estimation Under Correlated Noise

IEEE Access, 2022
Optimization of sensor selection has been studied to monitor complex and large-scale systems with data-driven linear reduced-order modeling. An algorithm for greedy sensor selection is presented under the assumption of correlated noise in the sensor ...
Keigo Yamada, Yuji Saito, Taku Nonomura, Keisuke Asai   +3 more
doaj   +1 more source

Maximizing Submodular+Supermodular Functions Subject to a Fairness Constraint

Tsinghua Science and Technology
We investigate the problem of maximizing the sum of submodular and supermodular functions under a fairness constraint. This sum function is non-submodular in general. For an offline model, we introduce two approximation algorithms: A greedy algorithm and
Zhenning Zhang, Kaiqiao Meng, Donglei Du, Yang Zhou   +3 more
doaj   +1 more source

Approximation Algorithms for Maximization of k-Submodular Function Under a Matroid Constraint

Tsinghua Science and Technology
In this paper, we design a deterministic 1/3-approximation algorithm for the problem of maximizing non-monotone k-submodular function under a matroid constraint.
Yuezhu Liu, Yunjing Sun, Min Li
doaj   +1 more source

Extremality of submodular functions

Theoretical Computer Science, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +3 more sources

Metric learning with submodular functions

Neurocomputing, 2020
Abstract Most of the metric learning mainly focuses on using single feature weights with Lp norms, or the pair of features with Mahalanobis distances to learn the similarities between the samples, while ignoring the potential value of higher-order interactions in the feature space.
Jiajun Pan, Hoel Le Capitaine
openaire   +5 more sources

Near Optimal Dynamic Mobile Advertisement Offloading With Time Constraints

IEEE Access, 2019
Owing to the accuracy and flexibility, mobile advertising has become a very attractive marketing method based on smart mobile terminals. The more common mobile advertisement distribution methods are based on location and content.
Wanru Xu, Chaocan Xiang, Chang Tian
doaj   +1 more source

A Submodular Optimization Framework for Imbalanced Text Classification With Data Augmentation

IEEE Access, 2023
In the domain of text classification, imbalanced datasets are a common occurrence. The skewed distribution of the labels of these datasets poses a great challenge to the performance of text classifiers.
Eyor Alemayehu, Yi Fang
doaj   +1 more source