1 code implementation • 16 Feb 2024 • Siamak Ghodsi, Seyed Amjad Seyedi, Eirini Ntoutsi
Conventional fair graph clustering methods face two primary challenges: i) They prioritize balanced clusters at the expense of cluster cohesion by imposing rigid constraints, ii) Existing methods of both individual and group-level fairness in graph partitioning mostly rely on eigen decompositions and thus, generally lack interpretability.
1 code implementation • 31 Dec 2020 • Reyhaneh Abdollahi, Seyed Amjad Seyedi, Mohamad Reza Noorimehr
Graph clustering is a fundamental task in the network analysis, which is essential for many modern applications.
2 code implementations • 8 Oct 2019 • Seyed Amjad Seyedi, S. Siamak Ghodsi, Fardin Akhlaghian, Mahdi Jalili, Parham Moradi
The major challenge of learning from multi-label data has arisen from the overwhelming size of label space which makes this problem NP-hard.
1 code implementation • 1 Jan 2019 • Seyed Amjad Seyedi, Abdulrahman Lotfi, Parham Moradi, Nooruldeen Nasih Qader
The cut-off distance affects the local density values and is calculated in different ways depending on the size of the datasets, which can influence the quality of clustering.
1 code implementation • 2 Jan 2017 • Abdulrahman Lotfi, Seyed Amjad Seyedi, Parham Moradi
In the second step, a novel label propagation method is proposed to form clusters.