ofsoundof/group_sparsity

Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. CVPR2020.

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KentonMurray/ProxGradPytorch

PyTorch implementation of Proximal Gradient Algorithms a la Parikh and Boyd (2014). Useful for Auto-Sizing (Murray and Chiang 2015, Murray et al. 2019).

Language: Python - Size: 32.2 KB - Last synced at: about 12 hours ago - Pushed at: almost 5 years ago - Stars: 42 - Forks: 5

matthieumeo/pyoneer

Pyoneer is a Python 3 package for the continuous recovery of non-bandlimited periodic signals with finite rates of innovation (e.g. Dirac streams) from generalised measurements.

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alexshtf/inc_prox_pt

Proximal-point methods for machine learning

Language: Python - Size: 1.09 MB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 6 - Forks: 0

fby1997/Lasso-Regression-coordinate-gradient-descent-proximal-gradient-and-ADMM-Ridge-Regression

Use Ridge Regression and Lasso Regression in prostate cancer data

Language: Python - Size: 16.6 KB - Last synced at: about 1 year ago - Pushed at: over 5 years ago - Stars: 5 - Forks: 3

jameschapman19/scikit-prox

A package for fitting regularized models from scikit-learn via proximal gradient descent

Language: Python - Size: 104 KB - Last synced at: 12 days ago - Pushed at: almost 2 years ago - Stars: 4 - Forks: 0

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

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

Language: Python - Size: 2 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 4 - Forks: 0

jameschapman19/proxtorch

An efficient GPU-compatible library built on PyTorch, offering a wide range of proximal operators and constraints for optimization and machine learning tasks.

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mrsamsami/Convex-Optimization

Implementation and analysis of convex optimization algorithms

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xianchen2/lasso_ProximalGD_Accelerated_ADMM

Python Implementations of proximal GD, Accelerated proximal GD and ADMM for solving lasso regression

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qntwrsm/ProximalMethods.jl

Provides proximal operator evaluation routines and proximal optimization algorithms, such as (accelerated) proximal gradient methods and alternating direction method of multipliers (ADMM), for non-smooth/non-differentiable objective functions.

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EliaFantini/CSI-using-Blind-Image-Deconvolution-and-Frank-Wolfe-algorithm

Blind Image Deconvolution and Frank-Wolfe's algorithm to deblur a license plate for Crime Scene Investigation (CSI)

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sam255/FISTA-in-Julia

Language: Julia - Size: 88.9 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

joelbengs/optimization_for_learning_with_pytorch

[Optimization algorithms] Study of the Proximal Gradient Method, Stochastic Gradient Descent method and Adam optimizer

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lumeilevel/MGProx

Reproduction for 2302.04077

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EliaFantini/FO-PROX-first-order-and-proximal-methods-convergence-comparison

Implementation and brief comparison of different First Order and different Proximal gradient methods, comparison of their convergence rates

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Niangmohamed/Optimization-for-Data-Science

Optimization methods for lasso penalized logistic regression.

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vienmai/pomodoro

Pomodoro: Progressive Decomposition Methods with Acceleration

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