This is a collaboration work initiated by my colleague Dr Daphne and Prof Nadimi. In this work, we adapt the Multi-Trial Vector-based Differential Evolution (MTDE) in clustering algorithm. MTDE is an optimization technique proposed by Prof Nadimi’s group.
Automatic Deep Clustering based on Multi-Trial Vector-based Differential Evolution (MTDE)
This is Parham’s side project during his time as a PhD student in UBD.
People
- Parham Hadikhani
- Daphne Teck Ching Lai (main supervisor)
- Mohammad H. Nadimi-Shahraki
- Ong Wee Hong
Data/Codes
Publications
- Parham Hadikhani, Daphne Teck Ching Lai, Wee-Hong Ong, Mohammad H. Nadimi-Shahraki, Automatic Deep Sparse Multi-Trial Vector-based Differential Evolution clustering with manifold learning and incremental technique, Image and Vision Computing, Volume 136, 2023, 104712, ISSN 0262-8856, https://doi.org/10.1016/j.imavis.2023.104712 (pdf)
- Parham Hadikhani, Daphne Teck Ching Lai, Wee-Hong Ong, and Mohammad H. Nadimi-Shahraki. 2022. Improved data clustering using multi-trial vector-based differential evolution with gaussian crossover. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO ’22). Association for Computing Machinery, New York, NY, USA, 487–490. https://doi.org/10.1145/3520304.3528885 (pdf)