MetaMF
Matrix factorization algorithm
This repository provides an implementation of the Meta Matrix Factorization algorithm for federated rating predictions in distributed data settings.
17 stars
1 watching
2 forks
Language: Jupyter Notebook
last commit: over 4 years agoRelated projects:
| Repository | Description | Stars |
|---|---|---|
| An implementation of an algorithm for factoring integers using quantum computing and optimization techniques | 50 | |
| A software framework for nonnegative matrix factorization and its application to multi-modal omics data analysis | 17 | |
| A software implementation of a matrix factorization technique to fuse graph structure and content into node embeddings. | 20 | |
| An implementation of Factorization Machine with arbitrary order and multiple optimization methods | 780 | |
| A framework for incorporating uncertainty quantification into federated learning models | 10 | |
| Provides a collection of algorithms for nonnegative matrix and tensor factorizations. | 57 | |
| An advanced C++ template metaprogramming framework for working with sequences and algorithms. | 164 | |
| A TensorFlow implementation of an HMM layer with algorithms for forward/backward and viterbi decoding | 287 | |
| Provides a Matlab implementation of an image fusion technique using multi-scale patch decomposition | 44 | |
| Measures the performance of deep learning models in various deployment scenarios. | 1,256 | |
| An algorithm for Federated Learning that handles client subsampling and data heterogeneity with unbounded smoothness | 0 | |
| A Python library implementing matrix profile algorithms for time series data mining tasks | 363 | |
| An algorithm that uses deep learning to factorize large matrices and identify overlapping communities in networks | 22 | |
| A library providing optimized algorithms for matrix factorization in machine learning applications | 1,078 | |
| An algorithm for Federated Learning with heterogeneous data, designed to optimize deep neural networks and improve performance | 2 |