12 citations · 30 across the 10 of their papers we have counts for
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math.NA2019
VeST: Very Sparse Tucker Factorization of Large-Scale Tensors
Moonjeong Park, Jun-Gi Jang, Lee Sael
Given a large tensor, how can we decompose it to sparse core tensor and factor matrices such that it is easier to interpret the results? How can we do this without reducing the acc…
math.NA2018★ 12 cited
Zoom-SVD: Fast and Memory Efficient Method for Extracting Key Patterns in an Arbitrary Time Range
Jun-Gi Jang, Dongjin Choi, Jinhong Jung +1
Given multiple time series data, how can we efficiently find latent patterns in an arbitrary time range? Singular value decomposition (SVD) is a crucial tool to discover hidden fac…
math.NA2017★ 6 cited
Fast, Accurate, and Scalable Method for Sparse Coupled Matrix-Tensor Factorization
Dongjin Choi, Jun-Gi Jang, U Kang
How can we capture the hidden properties from a tensor and a matrix data simultaneously in a fast, accurate, and scalable way? Coupled matrix-tensor factorization (CMTF) is a major…