Sparse Optimisation Research Code
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Updated
Apr 29, 2024 - Python
Sparse Optimisation Research Code
Robust PCA implementation and examples (Matlab)
Implemented ADMM for solving convex optimization problems such as Lasso, Ridge regression
Proximal operators for nonsmooth optimization in Julia
Proximal algorithms for nonsmooth optimization in Julia
Scientific Computational Imaging COde
Prune DNN using Alternating Direction Method of Multipliers (ADMM)
Implementation of the paper, "LIME: Low-Light Image Enhancement via Illumination Map Estimation"
A generic optimization method for any integer programming problem
An open-source MATLAB® ADMM solver for partially decomposable conic optimization programs.
It is a blueprint to data science from the mathematics to algorithms. It is not completed.
MATLAB library of gradient descent algorithms for sparse modeling: Version 1.0.3
Code for paper "A Distributed ADMM Approach for Collaborative Regression Learning in Edge Computing"
TOmographic MOdel-BAsed Reconstruction (ToMoBAR) software
Lensless imaging toolkit. Complete tutorial: https://go.epfl.ch/lenslesspicam
[ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Liu, Zhangyang Wang
CAE-ADMM: Implicit Bitrate Optimization via ADMM-Based Pruning in Compressive Autoencoders
A sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).
Experiments to speed up ADMM optimization algorithm for linear & semidefinite programming
Simulation code of our paper in IEEE Transactions on Cognitive Communications and Networking: ''Energy-Efficient Blockchain-enabled User-Centric Mobile Edge Computing''
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