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foolwood / pytorch-slimming

Learning Efficient Convolutional Networks through Network Slimming, In ICCV 2017.

deep-learning pytorch weight-pruning l1-regularization fast-inference

Updated May 13, 2019
Python

carnotresearch / cr-sparse

Functional models and algorithms for sparse signal processing

functional-programming lasso sparse-linear-systems convex-optimization sparse-bayesian-learning linear-operators compressive-sensing wavelets sparse-representations jax l1-regularization basis-pursuit

Updated Oct 17, 2023
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rfeinman / pytorch-lasso

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L1-regularized least squares with PyTorch

pytorch lasso least-squares sparse-coding dictionary-learning l1-regularization

Updated Feb 19, 2023
Python

sandipanpaul21 / Logistic-regression-in-python

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Logistic Regression technique in machine learning both theory and code in Python. Includes topics from Assumptions, Multi Class Classifications, Regularization (l1 and l2), Weight of Evidence and Information Value

logistic-regression regularization information-value weight-of-evidence ridge-regression l2-regularization lasso-regression multiclass-logistic-regression l1-regularization elastic-net-regression logistic-regression-assumptions

Updated Dec 22, 2021
Jupyter Notebook

mansipatel2508 / Network-Intrusion-Detection-with-Feature-Extraction-ML

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The given information of network connection, model predicts if connection has some intrusion or not. Binary classification for good and bad type of the connection further converting to multi-class classification and most prominent is feature importance analysis.

feature-selection rfc feature-extraction confusion-matrix roc-curve binary-classification l2-regularization network-intrusion-detection multiclass-classification feature-importance l1-regularization rfe pearson-correlation-coefficient fclassif select-percentile extrat-tree-classifier

Updated Aug 10, 2019
Jupyter Notebook

malena1906 / Pruning-Weights-with-Biobjective-Optimization-Keras

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Overparameterization and overfitting are common concerns when designing and training deep neural networks. Network pruning is an effective strategy used to reduce or limit the network complexity, but often suffers from time and computational intensive procedures to identify the most important connections and best performing hyperparameters. We s…

machine-learning sparsity ai tensorflow keras python3 image-classification automl l1-regularization network-compression unstructured-weight-pruning multiobjective-learning soft-pruning stochastic-multi-gradient dichotomic-serach dense-layers

Updated Sep 1, 2020
Python

EliaFantini / Image-Reconstructor-FISTA-proximal-method-on-wavelets-transform

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An Image Reconstructor that applies fast proximal gradient method (FISTA) to the wavelet transform of an image using L1 and Total Variation (TV) regularizations

python data-science machine-learning image-reconstruction pytorch matplotlib optimization-methods fista denoising-images skimage proximal-policy-optimization total-variation l1-regularization total-variational-denoising proximal-gradient-descent ista

Updated Sep 25, 2022
Python

jaydu1 / SparsePortfolio

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High Dimensional Portfolio Selection with Cardinality Constraints

portfolio-optimization l1-regularization cardinality-constraints high-dimensional-statistics

Updated Sep 27, 2022
Python

Arijit-datascience / CNN_BatchNormalization_Regularization

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MNIST Digit Prediction using Batch Normalization, Group Normalization, Layer Normalization and L1-L2 Regularizations

cnn pytorch dropout regularization l1-regularization groupnormalization groupnorm batchnormalization layernorm

Updated Jun 11, 2021
Jupyter Notebook

jajokine / Genomics-and-High-Dimensional-Data

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MITx - MicroMasters Program on Statistics and Data Science - Data Analysis: Statistical Modeling and Computation in Applications - Second Project

genomics logistic-regression regularization principal-component-analysis kmeans-clustering l2-regularization hierarchical-clustering genomics-visualization clustering-methods clustering-analysis l1-regularization genomics-data

Updated May 14, 2022
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ivannz / l1_tf

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A wrapper for L1 trend filtering via primal-dual algorithm by Kwangmoo Koh, Seung-Jean Kim, and Stephen Boyd

filter trend l1-regularization primal-dual-algorithm

Updated Jun 29, 2018
C

giamuhammad / neuralnet_optimization_based_on_ga

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Forecasting for AirQuality UCI dataset with Conjugate Gradient Artificial Neural Network based on Feature Selection L1 Regularized and Genetic Algorithm for Parameter Optimization

optimization genetic-algorithm forecasting artificial-neural-networks predictive-modeling regression-models conjugate-gradient-descent l1-regularization

Updated Jun 23, 2018
Jupyter Notebook

DolbyUUU / regression_algorithm_implementation_python

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regression algorithm implementaion from scratch with python (least-squares, regularized LS, L1-regularized LS, robust regression)

python regression regularization maximum-likelihood-estimation lasso-regression quantile-regression robust-regresssion l1-regularization ordinary-least-squares l2regularization

Updated Mar 2, 2023
Python

MoinDalvs / Different_types_Linear_Regressions

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data-science linear-regression linear ridge-regression polynomial-regression l2-regularization lasso-regression l1-regularization

Updated May 30, 2022
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aliyzd95 / Optimization-and-Regularization-from-scratch

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Implementation of optimization and regularization algorithms in deep neural networks from scratch

deep-neural-networks deep-learning optimization regularization gradient-descent cifar optimization-algorithms cifar10 adam l2-regularization adagrad rmsprop cifar-10 l1-regularization regularization-methods

Updated Nov 23, 2022
Python

federicoarenasl / Regularization-techniques-on-NNs

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During this study we will explore the different regularisation methods that can be used to address the problem of overfitting in a given Neural Network architecture, using the balanced EMNIST dataset.

data-science machine-learning deep-learning dropout neural-networks l2-regularization l1-regularization