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Robust and scalable PCA using Grassmann averages, in C++ with Matlab bindings

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Hi, I'm having difficulty compiling the tests for the project. I've tried a few different versions of boost, but none earlier than `1.55`. I cannot compile `CMakeFiles/GrassmannAveragesPCA_test.dir/test/test_row_proxy.cpp.o` which fails with...

grassmann_pca.hpp(687): error C2780: 'boost::_bi::bind_t boost::bind(M T::\* ,A1)': expects 2 arguments - 3 provided E:\ThirdPartyLibraries_VS2015\64Bit\boost-1_59\include\boost-1_59\boost/bind/bind.hpp(2018): note: see declaration of 'boost::bind' G:\Work_Dump\Integrated_Pipeline\src\Utilities\DimensionalityReduction\Linear\PCA\GrassmannPCA\GrassmannPCA.cpp(93): note: see reference to function template instantiation 'bool grassmann_averages_pca::grassmann_pca::batch_process(const size_t,size_t,const...