dlADMM: Deep Learning Optimization via Alternating Direction Method of Multipliers
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Updated
Apr 12, 2023 - Python
dlADMM: Deep Learning Optimization via Alternating Direction Method of Multipliers
Python routines to compute the Total Variation (TV) of 2D, 3D and 4D images on CPU & GPU. Compatible with proximal algorithms (ADMM, Chambolle & Pock, ...)
A re-implementaion of Professor Stanley Chan's Plug and Play ADMM Paper created for Professor Qi Guo's machine learning class at Purdue University
convex optimization
Alternating Direction Method of Multipliers (ADMM) for distributed budget allocation.
ADMM for Class-Imbalanced Training of Binary Image Classifiers
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