There are 1 repository under large-scale-learning topic.
Gradually-Warmup Learning Rate Scheduler for PyTorch
Riemannian stochastic optimization algorithms: Version 1.0.3
Scaling Object Detection by Transferring Classification Weights
i-RIM applied to the fastMRI challenge data.
Code for reproducing the experiments on large-scale pre-training and transfer learning for the paper "Effect of large-scale pre-training on full and few-shot transfer learning for natural and medical images" (https://arxiv.org/abs/2106.00116)
LIBS2ML: A Library for Scalable Second Order Machine Learning Algorithms
Fast Factorization Machines
Network of Experts for Large-Scale Image Categorization [ECCV 2016]
Enitor provides the MATLAB implementation of several large-scale kernel methods.
A distributed implementation of "Nested Subtree Hash Kernels for Large-Scale Graph Classification Over Streams" (ICDM 2012).
Machine Learning Platform Based on PS-Lite
Universal ML: Large Scale Distributed Machine Learning (Deep Learning) Systems
Falkon is one of the most efficient algorithm able to work in a supervised large scale setting. This method is the result of a combination of three simple principles: sub-sampling, preconditioning and iterative solvers. In order to extend FALKON usability we have designed an extension able to work in a semi-supervised scenario.
A curated list of papers on large-scale graph learning.
Machine learning course by Andrew Ng
Make HTS Forecasting paper implemented on a M5 dataset
Java based Convolutional Neural Network package running on Apache Spark framework
Tutorials on optimizers for deep neural networks
R package: Hidden Markov Model for Bayesian Inference of large-scale mean and variance testing
Repository for non-Mercer multiclass EFS-LS-MCM presented in IJCNN 2018
My thesis