Mohadeseh Ganji

According to our database, Mohadeseh Ganji authored at least 9 papers between 2015 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Modelling Zeros in Blockmodelling.

Laurence A. F. Park, Mohadeseh Ganji, Emir Demirovic, Jeffrey Chan, Peter J. Stuckey, James Bailey, Christopher Leckie, Rao Kotagiri

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

2018

Image Constrained Blockmodelling: A Constraint Programming Approach.

Mohadeseh Ganji, Jeffrey Chan, Peter J. Stuckey, James Bailey, Christopher Leckie, Kotagiri Ramamohanarao, Ian Davidson

Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Semi-supervised Blockmodelling with Pairwise Guidance.

Mohadeseh Ganji, Jeffrey Chan, Peter J. Stuckey, James Bailey, Christopher Leckie, Kotagiri Ramamohanarao, Laurence A. F. Park

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Cluster-Based Crowd Movement Behavior Detection.

Meng Yang, Lida Rashidi, Aravinda S. Rao, Sutharshan Rajasegarar, Mohadeseh Ganji, Marimuthu Palaniswami, Christopher Leckie

Proceedings of the 2018 Digital Image Computing: Techniques and Applications, 2018

Lagrangian Constrained Community Detection.

Mohadeseh Ganji, James Bailey, Peter J. Stuckey

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Semi-supervised community detection and clustering.

Mohadeseh Ganji

PhD thesis, 2017

A Declarative Approach to Constrained Community Detection.

Mohadeseh Ganji, James Bailey, Peter J. Stuckey

Proceedings of the Principles and Practice of Constraint Programming, 2017

2016

Lagrangian Constrained Clustering.

Mohadeseh Ganji, James Bailey, Peter J. Stuckey

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

2015

Generalized Modularity for Community Detection.

Mohadeseh Ganji, Abbas Seifi, Hosein Alizadeh, James Bailey, Peter J. Stuckey

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015