3 citations · 7 across the 22 of their papers we have counts for
5 papers · 1 filter
Sobolev acceleration for neural networks
Jong Kwon Oh, Hanbaek Lyu, Hwijae Son
Sobolev training, which integrates target derivatives into the loss functions, has been shown to accelerate convergence and improve generalization compared to conventional tr…
Complexity of Block Coordinate Descent with Proximal Regularization and Applications to Wasserstein CP-dictionary Learning
Dohyun Kwon, Hanbaek Lyu
We consider the block coordinate descent methods of Gauss-Seidel type with proximal regularization (BCD-PR), which is a classical method of minimizing general nonconvex objectives…
Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data
Hanbaek Lyu, Georg Menz, Deanna Needell +1
Online nonnegative matrix factorization (ONMF) is a matrix factorization technique in the online setting where data are acquired in a streaming fashion and the matrix factors are u…
COVID-19 Time-series Prediction by Joint Dictionary Learning and Online NMF
Hanbaek Lyu, Christopher Strohmeier, Georg Menz +1
Predicting the spread and containment of COVID-19 is a challenge of utmost importance that the broader scientific community is currently facing. One of the main sources of difficul…
Online matrix factorization for Markovian data and applications to Network Dictionary Learning
Hanbaek Lyu, Deanna Needell, Laura Balzano
Online Matrix Factorization (OMF) is a fundamental tool for dictionary learning problems, giving an approximate representation of complex data sets in terms of a reduced number of…