Efficient Structure Learning of Bayesian Networks using Constraints

By Qiang Ji. Journal of machine learning research, 2011

298 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/a9cf1c8408a35fd0b94b5a2deef79f44cdeec338

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yu-Gang Jiang
2. Shih-Fu Chang
3. Subhabrata Bhattacharya
4. Joe Naoum-Sawaya
5. Mubarak Shah
6. Bissan Ghaddar
7. Claudio Gambella
8. Luc Van Gool

In Computational Theory and Mathematics

1. Joe Naoum-Sawaya
2. Mubarak Shah
3. Bissan Ghaddar
4. Claudio Gambella
5. Shih-Fu Chang

In Management Science and Operations Research

1. Joe Naoum-Sawaya
2. Mubarak Shah
3. Yu-Gang Jiang
4. Bissan Ghaddar
5. Claudio Gambella
6. Shih-Fu Chang

Citations in the corpus

• Optimization Models for Machine Learning: A Survey (2019, methodology): “The objective function (133) maximizes the score of the ascyclic graph where si() is a score function that can be efficiently computed for every node i ∈ N [51].”
• High-level event recognition in unconstrained videos (2012, background): “de Campos and Ji [18] proposed an efficient algorithm which integrates several structural constraints for learning Bayesian Networks.”