Results 11 to 20 of about 9,788 (160)

Some Results about the Contractions and the Pendant Pairs of a Submodular System [PDF]

Sahand Communications in Mathematical Analysis, 2019
Submodularity is an important  property of set functions with deep theoretical results  and various  applications. Submodular systems appear in many applicable area, for example machine learning, economics, computer vision, social science, game theory ...
Saeid Hanifehnezhad, Ardeshir Dolati
doaj   +1 more source

Efficient Streaming Algorithms for Maximizing Monotone DR-Submodular Function on the Integer Lattice

Mathematics, 2022
In recent years, the issue of maximizing submodular functions has attracted much interest from research communities. However, most submodular functions are specified in a set function.
Bich-Ngan T. Nguyen, Phuong N. H. Pham, Van-Vang Le, Václav Snášel   +3 more
doaj   +1 more source

Submodular Optimization Over Sliding Windows [PDF]

Proceedings of the 26th International Conference on World Wide Web, 2017
Maximizing submodular functions under cardinality constraints lies at the core of numerous data mining and machine learning applications, including data diversification, data summarization, and coverage problems. In this work, we study this question in the context of data streams, where elements arrive one at a time, and we want to design low-memory ...
Epasto, Alessandro, Lattanzi, Silvio, Vassilvitskii, Sergei, Zadimoghaddam, Morteza   +3 more
openaire   +2 more sources

Flexible Reconfigurations of Brain Networks During Decisions With Predefined Versus Self-Generated Options. [PDF]

Hum Brain Mapp
Graph theoretic analysis of task‐based fMRI data showed that open‐ended decisions, where options need to be generated by decision‐makers, engaged distinct reconfigurations of hierarchically organized modular brain networks, compared to external menu‐based choices and a semantic retrieval task.
Wu Q, Zhang Z, Hsu M, Kayser AS.
europepmc   +2 more sources

Test Suite Reduction via Submodular Function Maximization [PDF]

Jisuanji kexue, 2021
As regression testing size and cost increase,test suite reduction becomes more important to promote its efficiency.Du-ring the selection of test suite subset,we are supposed to consider the representativeness and diversity of subset,and apply an ...
WEN Jin, ZHANG Xing-yu, SHA Chao-feng, LIU Yan-jun
doaj   +1 more source

Geometric Primitive-Guided UAV Path Planning for High-Quality Image-Based Reconstruction

Remote Sensing, 2023
Image-based refined 3D reconstruction relies on high-resolution and multi-angle images of scenes. The assistance of multi-rotor drones and gimbal provides great convenience for image acquisition.
Hao Zhou, Zheng Ji, Xiangyu You, Yuchen Liu, Lingfeng Chen, Kun Zhao, Shan Lin, Xiangxiang Huang   +7 more
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

Survey of Automatic Labeling Methods for Topic Models [PDF]

Jisuanji kexue yu tansuo, 2023
Topic models are often used in modeling unstructured corpora and discrete data to extract the latent topic. As topics are generally expressed in the form of word lists, it is usually difficult for users to understand the meanings of topics, especially ...
HE Dongbin, TAO Sha, ZHU Yanhong, REN Yanzhao, CHU Yunxia
doaj   +1 more source

Submodular Functions: Learnability, Structure, and Optimization [PDF]

SIAM Journal on Computing, 2018
Submodular functions are discrete functions that model laws of diminishing returns and enjoy numerous algorithmic applications. They have been used in many areas, including combinatorial optimization, machine learning, and economics. In this work we study submodular functions from a learning theoretic angle.
Balcan, Maria-Florina, Harvey, Nicholas J. A.   +1 more
openaire   +2 more sources

Optimal Distributed Submodular Optimization via Sketching [PDF]

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
We present distributed algorithms for several classes of submodular optimization problems such as k-cover, set cover, facility location, and probabilistic coverage. The new algorithms enjoy almost optimal space complexity, optimal approximation guarantees, optimal communication complexity (and run in only four rounds of computation), addressing major ...
MohammadHossein Bateni, Hossein Esfandiari, Vahab Mirrokni   +2 more
openaire   +1 more source