43 citations · 139 across the 21 of their papers we have counts for
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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★ 43 cited
Scalable Tucker Factorization for Sparse Tensors - Algorithms and Discoveries
Sejoon Oh, Namyong Park, Lee Sael +1
Given sparse multi-dimensional data (e.g., (user, movie, time; rating) for movie recommendations), how can we discover latent concepts/relations and predict missing values? Tucker…
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…