learning-rate

Two case studies: effects of changing the learning rate on model perfomance for image classificaiton, and cardiac failure prediction using clinical data

machine-learning deep-learning random-forest rstudio excel accuracy hospital ann learning-rate cnn-keras loss-functions svm-classifier cifar100 cardiac-indices

Updated Jan 14, 2024
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KhoiDOO / tvlars

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TVLARS - A Fast Convergence Optimizer for Large Batch Training

optimization optimization-algorithms learning-rate warmup learning-rate-scheduling layer-wise-relevance-propagation large-batch-optimization

Updated Nov 20, 2023
Python

Shahul-Rahman / MABSearch-Learning-the-learning-rate

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MABSearch: The Bandit Way of Learning the Learning Rate - A Harmony Between Reinforcement Learning and Gradient Descent

python machine-learning reinforcement-learning optimization global-optimization gradient-descent learning-rate multi-armed-bandit global-optimization-algorithms metaheuristics multiarm-bandit multiarmed-bandits global-minimum

Updated Oct 28, 2023
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GrHound / HyperparameterSteepness

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Enclosed is the steepness .c program with a bash script and .png graph for several steepness (alpha) values. As an example, the tolerance runs from 0.4 in the beginning to 0.01 at the end. You can make the binary by gcc steepness.c -lm -o steepness To run the demo script you need to install gnuplot The *.curves file and .png are already made. Yo…

machine-learning reinforcement-learning deep-learning robotics learning-rate continuous-curriculum-learning continuous-hyperparameter-schedule control-curve-steepness kohonen-som-learning-rate-curve

Updated Oct 4, 2023
C

harshalmittal4 / Hypergradient_variants

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Improved Hypergradient optimizers, providing better generalization and faster convergence.

momentum learning-rate adam-optimizer step-size optimizers hypergradient

Updated Apr 3, 2024
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KhaledAshrafH / Linear-Regression

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This program implements linear regression from scratch using the gradient descent algorithm in Python. It predicts car prices based on selected features and uses a dataset of cars with their respective prices.

linear-regression regression feature-selection dataset data-preprocessing regression-models learning-rate pyhton3 gredient-decent

Updated Aug 24, 2023
Python

kardasbart / MultiLR

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A method for assigning separate learning rate schedulers to different parameters group in a model.

deep-learning scheduler optimizer torch pytorch learning-rate lr lr-scheduling learning-rate-scheduling

Updated Jul 20, 2023
Python

kavilivishnu / Image_classification_using_the_CIFAR_10_dataset

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The main concentration of this project lies on image calssification using traditional CNN(Convolution Neural Networks), and also a couple of "BASE MODELS" such as "RestNet50", "DenseNet121" and "EfficientNetB0" that upgraded the performance of our CNN, followed by the Fully Connected NN, that we are using to train our model on.

image-classification regularization convolutional-neural-networks learning-rate resnet-50 base-models densenet121 epochs batchsize efficintnetb0

Updated Jul 7, 2023
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RajK01 / Google-Customer-Revenue-Prediction

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The main aim of this project is to built a predictive model using G Store data to predict the TOTAL REVENUE per customer that helps in better use of marketing budget.