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cs.LG2023
TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions
Taehyung Kwon, Jihoon Ko, Jinhong Jung +1
Many real-world datasets are represented as tensors, i.e., multi-dimensional arrays of numerical values. Storing them without compression often requires substantial space, which gr…
cs.LG2023
NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors
Taehyung Kwon, Jihoon Ko, Jinhong Jung +1
Many real-world data are naturally represented as a sparse reorderable matrix, whose rows and columns can be arbitrarily ordered (e.g., the adjacency matrix of a bipartite graph).…