Additional note of DPP source from MLNI repo

README.md

@@ -2,7 +2,7 @@
 
 ## Introduction
 
-This is the accompanying python code for the 2023 Information Processing in Medical Imaging (IPMI) Conference manuscript "[ Scalable Orthonormal Projective NMF via Diversified Stochastic Optimization](https://doi.org/10.1007/978-3-031-34048-2_38)". This implementation uses stochastic optimization using either random uniform sampling of determinantal point processes (DPP) to perform stochastic learning with orthonormal projective Nonnegative Matrix Factorization (opNMF from [Linear and Nonlinear Projective Nonnegative Matrix Factorization](https://doi.org/10.1109/TNN.2010.2041361)), reducing the memory footprint of the method and improving its scalability to big data. The opNMF implementation for neuroimaging context is a stripped down port of the matlab `opnmf.m` and `opnmf_mem.m` codes found at [brainparts github repository](https://github.com/asotiras/brainparts) to python. Portions of the DPP implementations were adapted [Dr. Alex Kulesza's matlab code](https://www.alexkulesza.com/) from [HYDRA github repository (in python)](https://github.com/evarol/HYDRA).
+This is the accompanying python code for the 2023 Information Processing in Medical Imaging (IPMI) Conference manuscript "[ Scalable Orthonormal Projective NMF via Diversified Stochastic Optimization](https://doi.org/10.1007/978-3-031-34048-2_38)". This implementation uses stochastic optimization using either random uniform sampling of determinantal point processes (DPP) to perform stochastic learning with orthonormal projective Nonnegative Matrix Factorization (opNMF from [Linear and Nonlinear Projective Nonnegative Matrix Factorization](https://doi.org/10.1109/TNN.2010.2041361)), reducing the memory footprint of the method and improving its scalability to big data. The opNMF implementation for neuroimaging context is a stripped down port of the matlab `opnmf.m` and `opnmf_mem.m` codes found at [brainparts github repository](https://github.com/asotiras/brainparts) to python. Portions of the DPP implementations were adapted matlab implementation at [Dr. Alex Kulesza's website](https://www.alexkulesza.com/), python implementation of DPP in [HYDRA github repository](https://github.com/evarol/HYDRA), and python implementation of DPP inside Hydra found at [MLNI github repository](https://github.com/anbai106/mlni).
 
 ## Prerequisites