In the morning, I learned about sparse codes. I got pretty stoked. We are finding that k-means (well not exactly k-means, which you should never use, but our generalization of it to be probabilistically correct) is too sparse to get good performance (on, say, explaining galaxy spectra), and we are finding that PCA (well not exactly PCA, which you should never use, but our generalization of it to be probabilistically correct) is too dense. Sparse codes looks like it might interpolate between these cases. That is, we will be able to capture more structure than a prototype approach, but not be as restricted as a linear manifold approach. Excited!
In the afternoon, Lang and I pair-coded and tested the (annoying) SDSS asTrans astrometric transformation meta-data format in Python. Soon all your SDSS interface will belong to us.