3 papers
cs.LG2026
Non-negative Matrix Factorisation with Topological Regularisation
Matias de Jong van Lier, Shizuo Kaji, Keunsu Kim
We investigate the learning of interpretable bases in non-negative matrix factorisation (NMF) by regularising the topology of the learned basis functions. Our approach is motivated…
math.OC2024
Filtration learning in exact multi-parameter persistent homology and classification of time-series data
Keunsu Kim, Jae-Hun Jung
To analyze the topological properties of the given discrete data, one needs to consider a continuous transform called filtration. Persistent homology serves as a tool to track chan…
stat.ML2024
Supervised low-rank semi-nonnegative matrix factorization with frequency regularization for forecasting spatio-temporal data
Keunsu Kim, Hanbaek Lyu, Jinsu Kim +1
We propose a novel methodology for forecasting spatio-temporal data using supervised semi-nonnegative matrix factorization (SSNMF) with frequency regularization. Matrix factorizati…