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LSTM and QRNN Language Model Toolkit for PyTorch
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Created
2017-08-08
40 commits to master branch, last one 2 years ago
NFNets and Adaptive Gradient Clipping for SGD implemented in PyTorch. Find explanation at tourdeml.github.io/blog/
Created
2021-02-13
80 commits to main branch, last one 2 years ago
MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
sgd
svrg
matlab
big-data
gradient
optimization
quasi-newton
classification
newtons-method
online-learning
machine-learning
linear-regression
variance-reduction
logistic-regression
softmax-classification
optimization-algorithms
gradient-descent-algorithm
machine-learning-algorithms
stochastic-gradient-descent
stochastic-optimization-algorithms
Created
2016-10-26
133 commits to master branch, last one about a year ago
Machine learning algorithms in Dart programming language
sgd
dart
softmax
dartlang
algorithm
classifier
regression
data-science
hyperparameters
lasso-regression
machine-learning
linear-regression
softmax-algorithm
softmax-classifier
softmax-regression
logistic-regression
batch-gradient-descent
machine-learning-algorithms
mini-batch-gradient-descent
stochastic-gradient-descent
Created
2017-04-02
1,065 commits to master branch, last one 3 months ago
This repository contains the results for the paper: "Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers"
Created
2020-06-30
48 commits to master branch, last one 3 years ago
Keras/TF implementation of AdamW, SGDW, NadamW, Warm Restarts, and Learning Rate multipliers
Created
2019-09-27
53 commits to master branch, last one 2 years ago
A Deep Learning and preprocessing framework in Rust with support for CPU and GPU.
Created
2023-03-30
184 commits to main branch, last one about a year ago
A tour of different optimization algorithms in PyTorch.
Created
2020-11-14
22 commits to main branch, last one 3 years ago
Java based sample code for developing on Android. The demos in this repository are stored on separate branches. To navigate to a demo, please click branches.
Created
2017-07-11
8 commits to master branch, last one 2 years ago
PyTorch implementation of Federated Learning algorithms FedSGD, FedAvg, FedAvgM, FedIR, FedVC, FedProx and standard SGD, applied to visual classification. Client distributions are synthesized with arb...
Created
2022-01-05
204 commits to master branch, last one 2 years ago
Unofficial implementation of Switching from Adam to SGD optimization in PyTorch.
Created
2019-05-29
4 commits to master branch, last one 5 years ago
Riemannian stochastic optimization algorithms: Version 1.0.3
sgd
big-data
manifold
optimization
online-learning
machine-learning
variance-reduction
riemannian-manifold
large-scale-learning
stochastic-optimizers
nonlinear-optimization
non-convex-optimization
optimization-algorithms
riemannian-optimization
stochastic-optimization
constrained-optimization
machine-learning-algorithms
stochastic-gradient-descent
nonlinear-optimization-algorithms
Created
2018-07-12
63 commits to master branch, last one about a year ago
A C++ toolkit for Convex Optimization (Logistic Loss, SVM, SVR, Least Squares etc.), Convex Optimization algorithms (LBFGS, TRON, SGD, AdsGrad, CG, Nesterov etc.) and Classifiers/Regressors (Logistic ...
Created
2018-07-03
38 commits to master branch, last one 2 years ago
Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enforces privacy by clipping and sanitising the gradients with Gaus...
Created
2020-10-01
80 commits to master branch, last one 8 months ago
SGD with large step sizes learns sparse features [ICML 2023]
Created
2022-10-04
15 commits to master branch, last one about a year ago