LSTM and QRNN Language Model Toolkit for PyTorch
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Feb 12, 2022 - Python
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sgd
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NFNets and Adaptive Gradient Clipping for SGD implemented in PyTorch. Find explanation at tourdeml.github.io/blog/
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Jan 19, 2024 - Python
Efficient, transparent deep learning in hundreds of lines of code.
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Apr 25, 2019 - MATLAB
MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
machine-learning big-data optimization matlab linear-regression machine-learning-algorithms sgd classification logistic-regression gradient optimization-algorithms online-learning gradient-descent-algorithm variance-reduction stochastic-gradient-descent newtons-method stochastic-optimization-algorithms quasi-newton softmax-classification svrg
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May 11, 2023 - MATLAB
Machine learning algorithms in Dart programming language
dart classifier data-science machine-learning algorithm linear-regression machine-learning-algorithms regression hyperparameters sgd logistic-regression softmax-regression dartlang stochastic-gradient-descent softmax lasso-regression batch-gradient-descent mini-batch-gradient-descent softmax-classifier softmax-algorithm
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Sep 7, 2024 - Dart
Ternary Gradients to Reduce Communication in Distributed Deep Learning (TensorFlow)
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Nov 19, 2018 - Python
This repository contains the results for the paper: "Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers"
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Jul 17, 2021
Keras/TF implementation of AdamW, SGDW, NadamW, Warm Restarts, and Learning Rate multipliers
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Jan 6, 2022 - Python
A Deep Learning and preprocessing framework in Rust with support for CPU and GPU.
rust machine-learning deep-learning gpu opencl cuda nn ml pipelines regression dropout sgd neural-networks classification data-analysis gpu-computing adam nalgebra
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Oct 3, 2023 - Rust
A tour of different optimization algorithms in PyTorch.
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Dec 11, 2021 - Jupyter Notebook
Lua implementation of Entropy-SGD
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Apr 9, 2018 - Python
Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolution Layers https://arxiv.org/abs/1802.00124
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Nov 14, 2018 - Python
PyTorch implementation of Federated Learning algorithms FedSGD, FedAvg, FedAvgM, FedIR, FedVC, FedProx and standard SGD, applied to visual classification. Client distributions are synthesized with arbitrary non-identicalness and imbalance (Dirichlet priors). Client systems can be arbitrarily heterogeneous. Several mobile-friendly models are prov…
pytorch sgd classification heterogeneity federated-learning imbalance non-iid fedavg fedprox fedsgd fedavgm fedir fedvc
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Feb 27, 2022 - Python
Riemannian stochastic optimization algorithms: Version 1.0.3
machine-learning big-data optimization machine-learning-algorithms constrained-optimization sgd manifold nonlinear-optimization optimization-algorithms large-scale-learning online-learning stochastic-optimizers variance-reduction stochastic-gradient-descent nonlinear-optimization-algorithms stochastic-optimization riemannian-manifold riemannian-optimization non-convex-optimization
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Jan 5, 2023 - MATLAB
Distributed Learning by Pair-Wise Averaging
python distributed-systems deep-learning pytorch sgd neural-networks gossiping asynchronous-learning
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Oct 31, 2017 - Python
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 Regression, SVMs, Least Squares Regression etc.)
machine-learning machine-learning-algorithms sgd tron logistic-regression regularization gradient-descent support-vector-machines optimization-algorithms convex-optimization lbfgs-algorithm lbfgs jensen
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Feb 26, 2022 - C++
R/Rcpp implementation of the 'Follow-the-Regularized-Leader' algorithm
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Mar 26, 2018 - R
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