A General Collaborative Filtering Framework based on Matrix Bordered Block Diagonal Forms Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma State Key Laboratory of Intelligent Technology and Systems Department of Compute

Source URL: yongfeng.me

• Recommender systems
• Matrix theory
• Linear algebra
• Sparse matrices
• Multivariate statistics
• Non-negative matrix factorization
• Collaborative filtering
• GroupLens Research
• MovieLens
• Singular value decomposition
• Graph partition
• Matrix decomposition

Localized Matrix Factorization for Recommendation based on Matrix Block Diagonal Forms Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma, Shi Feng Tsinghua University, Beijing, China

Source URL: yongfeng.me

• Sparse matrices
• Matrix theory
• Matrices
• Block matrix
• Matrix
• Sparse matrix
• Non-negative matrix factorization
• Graph partition

HIERATIC WP3:
 
 Algorithms for Identifying
 Linear Coarse Grainings


Source URL: www.hieratic.eu

• Linear algebra
• Matrix theory
• Sparse matrices
• Matrices
• Matrix
• Eigenvalues and eigenvectors
• Diagonal matrix
• Invariant subspace
• Invariant
• Block matrix

Fakultät für Informatik der Technischen Universität München Bachelorarbeit in Informatik

Source URL: www5.in.tum.de

• Sparse matrices
• Binary operations
• Numerical linear algebra
• Matrices
• Matrix theory
• Matrix
• Sparse matrix
• Cache-oblivious algorithm
• Block matrix
• Multiplication

Jonathan Scarlett and Volkan Cevher Supplementary Material for “Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices” (AISTATS 2016, Jonathan Scarlett and Volkan Cevher) Note that all

Source URL: jmlr.org

The Sparse Matrices Package. Sparse Matrix Calculations and a Linear Algebra Package for Sparse Matrices in REDUCE Stephen Scowcroft Konrad-Zuse-Zentrum f¨ ur Informationstechnik Berlin

Source URL: www.reduce-algebra.com

Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices Jonathan Scarlett and Volkan Cevher Laboratory for Information and Inference Systems (LIONS) École Polytechnique Fédérale de Lausann

Source URL: jmlr.org

Package ‘irlba’ October 11, 2015 Type Package Title Fast Truncated SVD, PCA and Symmetric Eigendecomposition for Large Dense and Sparse Matrices Version 2.0.0

Source URL: cran.r-project.org

1 Sparse Recovery Using Sparse Matrices Anna Gilbert, Piotr Indyk Abstract—We survey algorithms for sparse recovery problems that are based on sparse random matrices. Such matrices

Source URL: people.csail.mit.edu

Deriving Efficient Parallel Implementations of Algorithms Operating on General Sparse Matrices using Automatic Program Transformation? Stephen Fitzpatrick1 , T. J. Harmer1 and J. M. Boyle2 1

Source URL: www.kestrel.edu