arXiv (All)
open access
Tensor CUR Decomposition under the Linear-Map-Based Tensor-Tensor Multiplication
The factorization of three-dimensional data continues to gain attention due to its relevance in representing and compressing large-scale datasets. The linear-map-based tensor-tensor multiplication is a matrix-mimetic operation that extends the notion of matrix multiplication to higher order tensors,
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- TIDE-MC: Two-Sided Interpolative Decomposition for Billion-Scale GPU Matrix Completion#423939
- Asymptotic Rank Speedup Theorems, Revisited#1063927
- Efficient Application of Tensor Network Operators to Tensor Network States Through Successive Deterministic Compression#1143674
- Structural Packing and Dyadic Factorization of Sparse Positive Definite Matrices#798603
- Structural Packing and Dyadic Factorization of Sparse Positive Definite Matrices#797190
Record · ID 984983
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive