Parameterized Low-Rank Binary Matrix Approximation
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Publication:5002728
DOI10.4230/LIPIcs.ICALP.2018.53zbMath1499.68151OpenAlexW2996901643MaRDI QIDQ5002728
Fahad Panolan, Petr A. Golovach, Fedor V. Fomin
Publication date: 28 July 2021
Full work available at URL: https://drops.dagstuhl.de/opus/volltexte/2018/9057/pdf/LIPIcs-ICALP-2018-53.pdf/
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Norms of matrices, numerical range, applications of functional analysis to matrix theory (15A60) Approximation algorithms (68W25) Boolean and Hadamard matrices (15B34) Parameterized complexity, tractability and kernelization (68Q27)
Related Items (2)
Parameterized \(k\)-clustering: tractability island ⋮ Low-Rank Binary Matrix Approximation in Column-Sum Norm.
Uses Software
Cites Work
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- Discovery of optimal factors in binary data via a novel method of matrix decomposition
- Reducing rank of the adjacency matrix by graph modification
- Fundamentals of parameterized complexity
- Nonnegative ranks, decompositions, and factorizations of nonnegative matrices
- Biclique coverings of regular bigraphs and minimum semiring ranks of regular matrices
- Non-negative matrix factorization techniques. Advances in theory and applications
- Application of separability and independence notions for proving lower bounds of circuit complexity
- Expressing combinatorial optimization problems by linear programs
- Optimal decompositions of matrices with grades into binary and graded matrices
- Tight bounds for parameterized complexity of cluster editing with a small number of clusters
- The complexity of the single individual SNP haplotyping problem
- Exponential Lower Bounds for Polytopes in Combinatorial Optimization
- Rank Reduction of Directed Graphs by Vertex and Edge Deletions
- Generalized Independent Component Analysis Over Finite Alphabets
- Approximating extent measures of points
- Randomized Algorithms for Matrices and Data
- Polynomial-time approximation schemes for geometric min-sum median clustering
- Closest Substring Problems with Small Distances
- Linear-time approximation schemes for clustering problems in any dimensions
- Approximate clustering via core-sets
- Spectral Algorithms
- Color-coding
- A Clustering Approach to Constrained Binary Matrix Factorization
- On the Parameterized Complexity of Biclique Cover and Partition
- Matrix Rigidity from the Viewpoint of Parameterized Complexity
- On Two Segmentation Problems
- Independent Component Analysis Over Galois Fields of Prime Order
- Learning the parts of objects by non-negative matrix factorization
- Weighted low rank approximations with provable guarantees
- Data reduction and exact algorithms for clique cover
- Computing a nonnegative matrix factorization -- provably
- Segmentation problems
- Parameterized Algorithms
- An Almost Optimal Algorithm for Computing Nonnegative Rank
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