Masahiro Kumagai (Kobayashi-Sato Lab., MC1), et. al received the Best Paper Award at The Eighth International Symposium on Computing and Networking (CANDAR 2020) for the presentation entitled

Combinatorial Clustering Based on an Externally-Defined One-Hot Constraint
by Masahito Kumagai, Kazuhiko Komatsu, Fumiyo Takano, Takuya Araki, Masayuki Sato, and Hiroaki Kobayashi

 

This paper proposes combinatorial clustering that overcomes the limitations of the method of the Lagrange multiplier. The proposed method uses a QUBO solver that can externally define the one-hot constraint independent from the objective function, and the externally-defined constraint is satisfied by the bit-flip operations. Since the constraint function is not included in the objective function, it is no longer needed to determine the Lagrange multiplier. The experimental results show that the proposed method can improve the quality of clustering results.

 

For more information
https://www.youtube.com/watch?v=ZaLDqJIWJ7c

 

For the contact information
https://www.cal.is.tohoku.ac.jp/_wp/en/