On the Variance of the Adaptive Learning Rate and Beyond
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Updated
Jul 31, 2021 - Python
On the Variance of the Adaptive Learning Rate and Beyond
ADAM - A Question Answering System. Inspired from IBM Watson
RAdam implemented in Keras & TensorFlow
Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games
Adam (or adm) is a coroutine-friendly Android Debug Bridge client written in Kotlin
Learning Rate Warmup in PyTorch
A tour of different optimization algorithms in PyTorch.
Addon which enhances all user profiles of confluence. It also adds an advanced people directory. The whole addon is configurable by means of an XML, can be localized, supports Velocity templates and supports view and edit restrictions.
Easy-to-use AdaHessian optimizer (PyTorch)
Deep learning projects including applications (face recognition, neural style transfer, autonomous driving, sign language reading, music generation, translation, speech recognition and NLP) and theories (CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, hyperparameter tuning, regularization, optimization, Residual Networks). …
Easy-to-use linear and non-linear solver
ADAS is short for Adaptive Step Size, it's an optimizer that unlike other optimizers that just normalize the derivative, it fine-tunes the step size, truly making step size scheduling obsolete, achieving state-of-the-art training performance
Simple MATLAB toolbox for deep learning network: Version 1.0.3
Partially Adaptive Momentum Estimation method in the paper "Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks" (accepted by IJCAI 2020)
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