Projects that are tagged with singular value decomposition.


Logo Spectra. A Library for Large Scale Eigenvalue Problems 0.5.0

by yixuanq - September 13, 2017, 02:34:21 CET [ Project Homepage BibTeX Download ] 763 views, 239 downloads, 2 subscriptions

About: A header-only C++ library for solving large scale eigenvalue problems

Changes:

Initial Announcement on mloss.org.


About: A non-iterative, incremental and hyperparameter-free learning method for one-layer feedforward neural networks without hidden layers. This method efficiently obtains the optimal parameters of the network, regardless of whether the data contains a greater number of samples than variables or vice versa. It does this by using a square loss function that measures errors before the output activation functions and scales them by the slope of these functions at each data point. The outcome is a system of linear equations that obtain the network's weights and that is further transformed using Singular Value Decomposition.

Changes:

Initial Announcement on mloss.org.


About: A non-iterative learning method for one-layer (no hidden layer) neural networks, where the weights can be calculated in a closed-form manner, thereby avoiding low convergence rate and also hyperparameter tuning. The proposed learning method, LANN-SVD in short, presents a good computational efficiency for large-scale data analytic.

Changes:

Initial Announcement on mloss.org.


Logo redsvd 0.1.0

by hillbig - August 30, 2010, 18:13:55 CET [ Project Homepage BibTeX Download ] 6628 views, 1431 downloads, 1 subscription

About: redsvd is a library for solving several matrix decomposition (SVD, PCA, eigen value decomposition) redsvd can handle very large matrix efficiently, and optimized for a truncated SVD of sparse matrices. For example, redsvd can compute a truncated SVD with top 20 singular values for a 100K x 100K matrix with 10M nonzero entries in about two second.

Changes:

Initial Announcement on mloss.org.