Nuit Blanche: Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation

We have covered Manopt before several times ( tag Manopt). It now comes to Python. From the paper: Further successful applications of optimization on manifolds include matrix completion tasks (Vandereycken, 2013; Boumal and Absil, 2015), robust PCA (Podosinnikova et al., 2014), dimension reduction for independent component analysis (ICA) (Theis et al., 2009), kernel ICA (Shen et al., 2007) and similarity learning (Shalit et al., 2012). Many more applications to machine learning and other elds exist. While a full survey on the usefulness of these methods is well beyond the scope of this manuscript, we highlight that at the time of writing, a search for the term \manifold optimization" on the IEEE Xplore Digital Library lists 1065 results; the Manopt toolbox itself is referenced in 90 papers indexed by Google Scholar.