momentum-optimization-algorithm

zeke-xie/Positive-Negative-Momentum

[ICML 2021] The official PyTorch Implementations of Positive-Negative Momentum Optimizers.

skolai/nag-gs

NAG-GS: Nesterov Accelerated Gradients with Gauss-Siedel splitting

kinit-sk/overshoot

Overshoot: Taking advantage of future gradients in momentum-based stochastic optimization

SaiCodePro/DFSM-Det

Intelligent Detection for RIS-Assisted MIMO Systems: A First-and-Second Momentum Approach

AlbertoMarinelli/QRI-ELM-and-ELM-with-Standard-Momentum

In this project it is used a Machine Learning model based on a method called Extreme Learning, with the employment of L2-regularization. In particular, a comparison was carried out between: (A1) which is a variant of incremental extreme learning machine that is QRIELM and (A2) which is a standard momentum descent approach, applied to the ELM.

aliejabbari/Optimizations-ADAM-Momentum-SGD

Python code for Gradient Descent, Momentum, and Adam optimization methods. Train neural networks efficiently.

stxupengyu/Matrix-Factorization-for-Recommendation

Using Matrix Factorization/Probabilistic Matrix Factorization to solve Recommendation。矩阵分解进行推荐系统算法。

aahouzi/Simple_Document_Classification_From_Scratch

Simple Document Classification using Multi Class Logistic Regression & SVM Soft Margin from scratch

AsmaaEssamSultan/Optimization-Techniques-from-scratch

hager51/Numerical-Optimization

Numerical Optimization for Machine Learning & Data Science

Heba-Atef99/ML_optimization_algorithms

This is an implementation of different optimization algorithms such as: - Gradient Descent (stochastic - mini-batch - batch) - Momentum - NAG - Adagrad - RMS-prop - BFGS - Adam Also, most of them are implemented in vectorized form for multi-variate problems

mkgeiger/neural-network

Lightweight neural network library written in ANSI-C supporting prediction and backpropagation for Convolutional- and Fully Connected neural networks

mmaric27/BasicDNN

Generic L-layer 'straight in Python' fully connected Neural Network implementation using numpy.

aysekonus/ml_optimization_algorithms

Comparsion of Machine Learning optimization algorithms with MNIST dataset

Efesasa0/mlp-backprop-two-moons

EE456 2022 mini project implementation of two-moons problem using multi-layer-perceptron with back-propagation with analyzing performance of initializing methods and momentum rule

ravikumarchopra/DL-Assignment-1

This repository contains a python implementation of Feed Forward Neural Network with Backpropagation, along with the example scripts for training the network to classify images from mnist and fashion_mnist datasets from keras.

Shresth-Mehta/Neural_Networks_API

Machine Learning, Deep Learning Implementations