sergeyvoronin / LowRankMatrixDecompositionCodesLinks
RSVDPACK: Implementations of fast algorithms for computing the low rank SVD, interpolative and CUR decompositions of a matrix, using randomized sampling. Includes codes for single core (using GNU GSL), multi-core (using Intel MKL) and GPU (using NVIDIA CUDA/CULA) architectures.
☆94Updated 3 years ago
Alternatives and similar repositories for LowRankMatrixDecompositionCodes
Users that are interested in LowRankMatrixDecompositionCodes are comparing it to the libraries listed below
Sorting:
- Distributed NMF/NTF Library☆48Updated 10 months ago
- Randomized Dimension Reduction Library☆117Updated 4 years ago
- The git repository for the TT-Toolbox☆205Updated 8 months ago
- Proximal Operator Graph Solver☆89Updated 2 years ago
- TMAC: A Toolbox of Modern Async-Parallel, Coordinate, Splitting, and Stochastic Methods☆48Updated 8 years ago
- A Newton ADMM based solver for Cone programming.☆39Updated 8 years ago
- Backpropagate derivatives through the Cholesky decomposition☆58Updated 5 years ago
- A MATLAB toolbox for building first-order solvers for convex models.☆142Updated 3 years ago
- Sketching-based Distributed Matrix Computations for Machine Learning☆100Updated 7 years ago
- The Surprisingly ParalleL spArse Tensor Toolkit.☆73Updated 3 years ago
- Sample implementations of proximal operators☆194Updated 12 years ago
- Proximal algorithms made easy in Python☆59Updated 8 years ago
- ☆67Updated 7 years ago
- A lightweight accelerated proximal-gradient package for matlab☆34Updated 9 years ago
- Header-only version of RedSVD☆58Updated 11 years ago
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆33Updated 9 years ago
- The pMMF Multiresolution Matrix Factorization Library☆27Updated 7 years ago
- C++/Eigen implementation of fast randomized SVD☆23Updated 4 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- Frank-Wolfe optimization variants with a linear convergence rate☆22Updated 9 years ago
- A suite of stochastic optimization methods for solving the empirical risk minimization problem.☆17Updated 5 years ago
- A Python convex optimization package using proximal splitting methods☆116Updated last month
- Python/Cython wrapper for liblbfgs☆46Updated 7 years ago
- Software package for Hankel structured low-rank approximation☆34Updated 6 years ago
- Bayesian optimization in high-dimensions via random embedding.☆115Updated 12 years ago
- FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"☆30Updated 5 years ago
- A MATLAB interface for L-BFGS-B☆52Updated 8 years ago
- Fast, vectorized C++ implementation of K-Means using the Eigen matrix template library. Includes Matlab and Python interfaces.☆57Updated 8 years ago
- Randomized online matrix factorization☆140Updated 5 years ago
- High-performance Non-negative Matrix Factorizations (NMF) - Python/C++☆49Updated 7 years ago