Work

Computationally Efficient Active Learning of Gaussian Graphical Models

Year: 2024

Type: conference-paper

Source: 2018 52nd Asilomar Conference on Signals, Systems, and Computers

DOI: 10.1109/ieeeconf60004.2024.10942879

Authors: Abrar Zahin, Gautam Dasarathy

Institution: Arizona State University

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: closed

Funders: National Science Foundation, National Institutes of Health

Awards: CAREER: Learning and Leveraging the Structure of Large Graphs: Novel Theory and Algorithms, G9000093548

OpenAlex ID: W4409156535

FWCI:

Cites: 28

Cited by:

Related to: 10