AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights (ICLR 2021)
-
Updated
Jan 13, 2021 - Python
AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights (ICLR 2021)
🌹 Rose: Range-Of-Slice Equilibration PyTorch optimizer. Stateless optimization through range-normalized gradient updates.
This project implements optimizers for TensorFlow and Keras, which can be used in the same way as Keras optimizers. Machine learning, Deep learning
Unofficial implementation of the Adan optimizer with Schedule-Free
NEAT (Nash-Equilibrium Adaptive Training) is a Keras first optimizer for conflict aware training, with an explicit NumPy reference engine, a small practical API, and optional native CPU acceleration.
AeroAttention is an innovative, quantum-enhanced attention mechanism designed for transformer models. It offers optimized memory usage and accelerated computations, enabling scalable and efficient training for advanced neural network architectures
AixrOptima is an artificial intelligence startup that speeds up the process process by integrating quantum circuits.
Muon is an optimizer for hidden layers in neural networks
Don't tune the knee. Measure it.
A fast ML library for experimentation and training on consumer hardware
A NumPy based Neural Network Package Implementation
AdaRankGrad: Adaptive Gradient Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning
En el siguiente repositorio encontrarás material relacionado con optimizadores usados en metodologías de aprendizaje de maquina. In the following repository you'll find examples of optimizers used in machine learning methods
Mini party optimizer to find the best team composition base on player's inventory in Genshin Impact
To associate your repository with the optimizer-algorithms topic, visit your repo's landing page and select "manage topics."