Learning content similarity for music recommendation

Learning content similarity for music recommendation, TASLP 2011
by Brian McFee, Luke Barrington, and Gert Lanckriet

• Metric learning to rank (MLR) = tr (W) + C/n*\sum (err_q), s.t. \deta<W,\pi>  >= \deta(y) - err_q;  solve the above obj by cutting-plane opt. (i.e., structured SVM)
• Use top-\tau codeword histogram over mfcc as feature 
• Motivation of using top-\tau (something like soft assignment): counteract quantization errors 
• Experiment result shows this reduce the number of codewords needed
• Represent each histogram in a probability product kernel (PPK) space to better exploit the geometry of codeword histograms.
• Leads to better accuracy
• Visualize result using t-SNE (http://homepage.tudelft.nl/19j49/t-SNE.html)