A MATLAB library for sparse representation problems
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Updated
Jul 20, 2022 - MATLAB
A MATLAB library for sparse representation problems
Functional models and algorithms for sparse signal processing
Contains a wide-ranging collection of compressed sensing and feature selection algorithms. Examples include matching pursuit algorithms, forward and backward stepwise regression, sparse Bayesian learning, and basis pursuit.
Sparse representation solvers for P0- and P1-problems
C++/Eigen3 implementation of the L1-norm minimization using homotopy
π A Python repository showcasing optimization techniques for Machine Learning including LP, Newton's methods, LASSO, and convex optimization. ππ
Code related to Optimization Techniques
Extending Sparse Dictionary Learning Methods for Adversarial Robustness
Exploring the utility of surface approximation using non-radial basis functions.
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