Supervised low-rank semi-nonnegative matrix factorization with frequency regularization for forecasting spatio-temporal data

no code implementations • 15 Nov 2023 • Keunsu Kim, Hanbaek Lyu, Jinsu Kim, Jae-Hun Jung

We propose a novel methodology for forecasting spatio-temporal data using supervised semi-nonnegative matrix factorization (SSNMF) with frequency regularization.

Highly-scalable stochastic neuron based on Ovonic Threshold Switch (OTS) and its applications in Restricted Boltzmann Machine (RBM)

no code implementations • 21 Oct 2020 • Seong-il Im, Hyejin Lee, Jaesang Lee, Jae-Seung Jeong, Joon Young Kwak, Keunsu Kim, Jeong Ho Cho, Hyunsu Ju, Suyoun Lee

Interest in Restricted Boltzmann Machine (RBM) is growing as a generative stochastic artificial neural network to implement a novel energy-efficient machine-learning (ML) technique.